Length Of Rainy Season Research Articles

Assessment of the effect of rainfall variability on maize productivity in Kaduna State, Nigeria

Understanding the link between climate and crop productivity is very important in ensuring the future of food security in every part of the world. Rainfall especially in the dry tropical environment is one of the main factor affecting crop productivity. This article aimed to assess the effects of rainfall variability on maize productivity in Kaduna state, Nigeria. Annual rainfall and crop yield data were retrieved from the Nigerian Meteorological Agency (Nimet) and Kaduna Agricultural Development Project (KADP), Kaduna respectively. Pearson product-moment correlation and multiple regression analysis were used to determine and assess the relationship between the rainfall indices and maize yield. The results of the correlation revealed that Length of rainy season has the strongest effects on maize yield in the study area with correlation coefficients of 0.501. The regression analysis showed that the selected rainfall indices accounts for 61.6 percent influence on maize yield in the study area during the reference period (1999-2018). The study recommends the judicious use of weather and climate forecast. This will help the farmers in proper timing during the crop production activities and also the selection of suitable crops for production to reduce the indiscriminate waste of valuable resources.

Analysis of Rainfall Characteristics in Kaduna State, Nigeria from 1999 – 2018

In the present time of changing climate, rainfall provides a vital information for effective agricultural and water resource planning and management. This study aimed at analyzing the rainfall characteristics in Kaduna state, Nigeria. Rainfall data of 20 years from 1999-2018 were obtained from the National Water Resource Institute Kaduna for the study. Walter’s 1967 formula was used to calculate the rainfall Onset and Cessation dates while the Seasonality Index was calculated using the Walsh and Lawler’s 1981 method. Results obtained revealed a decrease in trend for rainfall Onset and Cessation, Annual Rainfall amounts and also a negative trend in the Seasonality Index of the study area. While the Length of rainy season shows a positive trend for the reference period. The study suggests in-depth research in areas related to crop-climate relationship, so that variety of crops with optimum yield potentials will be cultivated in the area to feed the increasing population. This will help to avoid the risks of hunger and related food insecurity in the study area.

Markov Chain Rainfall Probability Model and Rainy Season Length in Kendrapara District, Odisha for Efficient Crop Management Strategies

Systematic information on rainfall patterns and distribution is essential for crop selection, adopting improved agronomic practices, designing rainwater harvesting structures, and conserving rainwater. This study analyzed the probabilities of rainfall occurrence to know the rainfall onset, withdrawal, and rainy season length for different blocks of Kendrapara district, Odisha. The rainfall analysis showed that the kharif season shares 75-78% of annual rainfall with July and August being the wettest. Seasonal rainfall showed a significant increase during kharif season while the decreasing trend was observed during the rabi and summer seasons. Markov chain analysis showed that the weekly probability for 20-mm rainfall and consecutive two weeks is more than 70% during SMW 25-38. During the June-October period, assured rainfall at 80% probability is greater than 800 mm in four blocks, while in other blocks it ranged between 610-779 mm. Assured rainfall during the rabi and summer season is uncertain, however, a 105-126 mm rainfall is received in May in many blocks, useful for summer ploughing and green manure crops. Rainy season length analysis at an 80% probability level revealed that only in 14-16 weeks’ rain occurs, thereby, only short-duration paddy can be grown with lower risk. By utilizing October rainfall and conserved soil moisture, short-duration pulses/oilseeds could be grown in all the blocks. However, kharif paddy must be sown/transplanted at the optimum time

Changes and variability in rainfall onset, cessation, and length of rainy season in the IGAD region of Eastern Africa

Rainfall onset dates (ROD), rainfall cessation dates (RCD) and length of rainy season (LRS) are crucial for crop production and food security in Eastern Africa yet scantily documented. This paper seeks to investigate the spatial patterns of these parameters. Data used are Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS v2.0) and National Oceanic and Atmospheric Administration (NOAA) gridded temperature. Threshold of 1 mm for rainy day, 20 mm over 5 days with at least 3 rain days and dry spell not exceeding 7 days in the next 21 days were used to determine RODs. The Potential Evapotranspiration (PET) and Water Balance (WB) criteria were computed to determine RCDs. The differences between ROD and RCD were used in calculating LRS. The results showed early rainfall cessation over more than 30 counties in Kenya lead to shortened rainy season by 10–20 days during MAM season. Similarly, 20–40 days early onset dates are observed in most counties in upper Nile, Unity, and Jonglei states in South Sudan, while 20–40 days delayed rainfall onset was observed in Khartoum and southern parts of Nile state western Darfur, eastern and Aljazeera states in Sudan, most parts of Ethiopia and Eritrea districts during JJA season. Highlands of western and Nyanza region in Kenya, most parts of Uganda observed rainfall onset by March and no sign of cessation before November. Early cessation over northern Uganda districts was behind shortened LRS, furthermore, the early RODs over western and southwestern Uganda districts increased LRS. Prolonged dry conditions over northern Sudan, southeastern parts of South Sudan, northern Kenya, central Somalia, northern Darfour, Kordofan and northern parts of Sudan exacerbated by significant delayed onset and early cessation of rainfall. These findings are important for rain-fed agricultural planning and food security in the IGAD region of Eastern Africa.

Skills Assessment of Selected Supervised Machine Learning Algorithms in Predicting Seasonal Rainfall over Bauchi in Nigeria

An attempt is made to use four selected machine learning algorithms (MLAs) to predict the seasonal and monthly amount of rainfall over a Savana station in Nigeria. The four MLAs are the artificial neural network (ANN), Random Forest model (RFM), K-Nearest Neighbor (KNN), and kernel basis Support Vector Machine (SVM). Monthly mean rainfall and monthly mean air temperature data from June to October over a period of 34 years (1986-2019) were used and seventeen atmospheric variables are used to develop the model during training period. The period is divided into two, the training (1986 - 2013) and testing (2014 - 2019) periods. The results show that SVM and ANN better reproduce both monthly and annual rainfall amount over the study area by accessing their skills during training period and also having lowest RMSE and MAE during testing period. SVM is the most suitable among the four MLAs. Though, some show better results for specific month(s), the SVM and ANN summary yield 84% and 82% respectively of good forecasts for seasonal rainfall amount over Bauchi. The web interface was developed using R (ShinyR Package) programming has a very interactive and good graphical user interface (GUI) for user with little or no computer knowledge. It is recommended that the two MLAs can be used to predict monthly and seasonal rainfall over Savana climatic zone of West Africa using the seventeen input variables and hence other variables can be selected for forecasting other rainfall properties like onset, cessation and length of rainy season over West Africa sub-region. The results also show the importance and weight of each of the seventeen input variables has in reproducing the dependent variable and hence be useful in choosing which input variable can be used in further studying the dynamics of West African rain producing systems. Keywords : Machine Learning, rainfall amount, training period, error analysis. DOI: 10.7176/JEES/12-10-06 Publication date: October 31 st 2022

Impacts of Climate Change on Rainfall Amount, Onset and Length of Rainy Season over West Africa

Impacts of Climate Change on Rainfall Amount, Onset and Length of Rainy Season over West Africa

Onset, Cessation, and Seasonality of Rainfall during Monsoon in Gujarat State of India

Rainfall onset, cessation and its temporal rainfall distribution is very important for monsoon based crop production. Climatic timeseries data of 26 stations of Gujarat state were chosen for the study. Year wise agroclimatic onset, cessation, length, and seasonality of rainy season were determined. Long term average over the timeseries were considered as climatic normals to characterize rainfall pattern to support kharif crop production. Onset starts in South Gujarat from 8th June and it cover the entire state by 6th July at Kutch, with large variation. Cessation of rainy season ranges from 6th September to 21st September in Gujarat. Length of active rainy season prevails from 66 days (at Bhachau) to 96 days (at Ubharat) with state mean of 81 days. Most part of the state has seasonal rainfall regime with dry periods. Rainfall seasonality monsoon season in Gujarat has not changed significantly during recent past.

Effects of Environment on Productive Performance of Holstein-Friesian Dairy Cows in Three Agro-Ecological Regions of Zimbabwe

The level of performance in any livestock production enterprise is a function of genetic and non-genetic factors and their interaction. For the purpose of agricultural production decisions, Zimbabwe was divided into five agro-ecological zones (AEZ) according to rainfall intensity, distribution and length of rainy season. Commercial dairy production, based on specialist dairy breeds such as Holstein, Holstein-Friesian and Jersey, is confined to AEZ I, II, III and IV. The performance of these breeds in contrasting AEZ has not been determined. In this study, farm level data of 7562 Holstein-Friesian cows calving in the period 2003-2011 was used to compare milk yield and milk components across three contrasting AEZ of Zimbabwe. A Generalized Linear Model (GLM) was fitted to investigate the fixed effects of year, season and AEZ and random effects of days in milk (DIM) on milk production and component traits. The factors herd, agro-ecological zone, year and season had significant (P

An investigation into the future changes in rainfall onset, cessation and length of rainy season in the Oti River Basin, West Africa

An investigation into the future changes in rainfall onset, cessation and length of rainy season in the Oti River Basin, West Africa

Differential signal of change among multiple components of West African rainfall

Rainfall components likely differ in the magnitude and direction of their long-term changes for any given location, and some rainfall components may carry a greater regional signal of change than rainfall totals. This study evaluates the magnitude of change of multiple rainfall components relative to other components, and the greatest regions of change across all rainfall components in West Africa. Hourly rainfall data from the ERA5 reanalysis dataset was used to derive twelve rainfall components, which were evaluated for long-term means, interannual variability, and long-term changes. For rainfall totals and rainfall intensity, the central Sahel is witnessing increasing trends while the western Sahel is experiencing significant decreasing trends. In general, decreasing trends predominate in the study domain, especially in the northwestern Congo Basin, where annual rainfall is decreasing by 120 mm per decade. Importantly, rainfall frequency accounts for 49% of all significant grid-point trends for the whole domain. In contrast, rainfall totals account for 26% of all combined significant trends across the domain, while rainfall intensity (12.6%), rainy season length (9.5%), and seasonality (3.3%) account for the remaining signals of change. Most of the changes among the rainfall components are in the tropical wet and dry regions (59% of all significant trends); the Saharan and equatorial regions account for the least changes. This study finds evidence that rainfall frequency is changing more across the regions compared to rainfall totals and should be explored as rainfall inputs in climate models to potentially improve regional predictions of future rainfall.

Potential Impact of Climate Variability on Tea Farming on the Mambilla Plateau, Taraba State, Nigeria

This study examined the potential impact of climate variability on tea farming on the Mambilla Plateau, Taraba State, Nigeria. Data for this study was generated through primary and secondary sources. The primary data were generated from field observation. Secondary desk review of existing literature and online resources were used. Archival data on climatic elements were obtained from the Upper Benue River Basin Development Authority (UBRBDA) Meteorological stations at Gembu and Maisamari, both on the Mambilla plateau. The data was analyzed using inferential statistics such as simple correlation coefficient (r), regression and time series analysis. The result of the findings on the trends of annual rainfall in the study area shows that rainfall amount, length of rainy season (LRS) and relative humidity were decreasing, with late onset and cessation of rains in the area. The trend of maximum and minimum temperature as well as wind speed was increasing owing to increasing rate of deforestation in the area. Climate variability and change has both advantages and disadvantages to the growth and development of tea which ultimately affect its production. Variability in precipitation and temperature has considerable impacts on tea quality and yields by altering the quantities and types of pests and weeds in and around tea farms. The findings of the study reveal that the global surface temperature has changed and will continue to change in the nearest future. Hence, the need to devise suitable means of adaptation and mitigation to the challenges of climate change in the area. Based on the findings, the study recommends the use of improved tea crop variety, involvement of local communities in climate change adaptation strategies, increase dissemination of climate information and education of the farmers on most suitable local adaptation strategies.

Change in Climate Indices Using Bias-Adjusted CMIP5 Models: The Case Study of the Fatick Region, Senegal

This study analyses change in rainfall and temperature indices by 2035 and 2050 in Senegal, with a focus on the Fatick region. These parameters are crucial for understanding the impacts of anthropogenic climate change on some vital socio-economic sectors such as agriculture and water resources in this region. To this end, a multi model ensemble mean of 21 bias-adjusted global climate models participating in CMIP5 has been used. We considered two Representative Concentration Pathways (RCP4.5 and RCP8.5). The results indicate an increase of 0.7˚C for maximum and minimum temperature by 2035 compared to the reference period (1976 - 2005). By 2050, an increase of 1.4˚C (2˚C) is projected for RCP4.5 (RCP8.5). These increases in temperature are statistically significant at the 90% confidence level. Conversely, the mean rainy season length decreases from 95 to 85 days by 2035 and less than 80 days by 2050. These decreases in rainy season length are mainly due to a delayed rainy season onset by 2035 and 2050, with the ensemble mean projecting an onset in the second half of July by 2050 instead of around the middle of June. The changes in both the onset and the length of the rainy season are significant at the 90% confidence level. Our results show a slight decrease in seasonal cumulated total rainfall by 2035 and 2050. However, we note a slight increase in seasonal cumulated extreme rainfall. These future changes in climate indices could induce yield reduction and water resources availability. To reduce yield losses, it would be interesting to adopt longer season varieties and also diversify income-generating activities. Concerning water resources, many actions could be done such as carrying out water retention works, treatment and reuse of non-conforming water for agriculture and livestock to reduce pressure on the resource.

Long-term (35 Years) Rainy and Dry Season Characterization in Semiarid Northeastern Brazil

Abstract Uncertainties in the timing and quality of rainy season are a threat for food and water security, and also in terms of fire vulnerability. Then, understanding features associated to rainfall allows a climate characterization useful for climate and fire risk management. We used rainfall data series (1983-2018) from 15 meteorological stations to characterize the greatest conservation area of Brazilian-unique seasonally dry tropical forest Caatinga (northeastern Brazil). Accumulated anomalies in daily series were used to determine onset and end of rainy seasons. We also determined seasonal and annual rainfall (quality) and rain rate, and performed a dry season sub-classification. Results showed greater variability for end dates as compared to onset dates for rainy season. Droughts in the region are becoming more severe. We found a significant decreasing tendency of 7 mm/year on annual rainfall, of 0.3 mm/day per decade on rain rate, and an increase of 12 days per decade on consecutive dry days. Dry season length presented a 14-year periodicity and is related with previous but uncorrelated from posterior rainy season length. The complexity of the rainfall patterns is evidenced by the weak correlation we found between the amount of rainfall and the rainy season length.

ASSESSMENT OF RAINFALL VARIABILITY FOR SUSTAINABLE AGRICULTURE IN OWERRI, IMO STATE, NIGERIA

Rainfall variability and agricultural sustainability have been of major concern to the Climatologists, Agriculturists and farmers in general. The net potential effect of severe changes in rainfall pattern is the disruption in crop production leading to food insecurity, joblessness and poverty. As a major concern to increase food production, this study seeks to assess the rainfall variability in Owerri City with a view to enhancing agricultural sustainability. The study used rainfall data (1981-2018) from Nigerian Meteorological Agency. Correlation and Regression techniques were employed for analysis. The result shows that there is no significant relationship between the number of rainy days and annual amount of rainfall. Also, there is no significant relationship between the length of rainy season and number of rainy days in the study area. The study also shows four years forecast of rainfall in the study area. The result shows an evidence and upsurge of low agricultural produce, food insecurity and hunger in the nearest future, and therefore recommends some sustainable agricultural practices that can boost yield, good health and healthy environment and reduce the effect of climate change.

Changes in length of rainy season and rainfall extremes under moderate greenhouse gas emission scenario in the Vea catchment, Ghana

Abstract The economic implications of extreme climate changes are found to impact sub-Saharan Africa negatively. This study aimed to analyze projected changes in length of rainy season (LRS), and rainfall extreme indices at the Vea catchment, Ghana. The analysis was performed using high-resolution simulated rainfall data from the Weather Research and Forecasting (WRF) model under moderate greenhouse gas emission scenario for the period 2020–2049 relative to the 1981–2010 period. LRS was computed from the difference between rainfall onset and cessation dates, and its trends were assessed using Mann–Kendall test and Sen's slope estimator. Annual rainfall intensity and frequency indices were computed. Results showed an increase in mean LRS from 168 to 177 days, which was at a rate of 1 day/year in the future (2020–2049). The LRS increase would be more significant at northern and south-western parts of the catchment. Rainfall intensity and frequency indices are projected to increase at spatial scale across the catchment. Projected changes in rainfall extremes could increase the frequency and intensity of drought and flood events. Thus, it is necessary to integrate suitable climate change adaptation measures such as rainwater harvesting, flood control measures, and development of early warning systems in the planning process by decision-makers at the catchment.

Contrasting responses of woody and herbaceous vegetation to altered rainfall characteristics in the Sahel

Abstract. Dryland ecosystems are a major source of land cover, account for about 40% of Earth's terrestrial surface and net primary productivity, and house more than 30 % of the human population. These ecosystems are subject to climate extremes (e.g. large-scale droughts and extreme floods) that are projected to increase in frequency and severity under most future climate scenarios. In this modelling study we assessed the impact of single years of extreme (high or low) rainfall on dryland vegetation in the Sahel. The magnitude and legacy of these impacts were quantified on both the plant functional type and the ecosystem levels. In order to understand the impact of differences in the rainfall distribution over the year, these rainfall anomalies were driven by changing either rainfall intensity, event frequency or rainy-season length. The Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model was parameterized to represent dryland plant functional types (PFTs) and was validated against flux tower measurements across the Sahel. Different scenarios of extreme rainfall were derived from existing Sahel rainfall products and applied during a single year of the model simulation timeline. Herbaceous vegetation responded immediately to the different scenarios, while woody vegetation had a weaker and slower response, integrating precipitation changes over a longer timeframe. An increased season length had a larger impact than increased intensity or frequency, while impacts of decreased rainfall scenarios were strong and independent of the season characteristics. Soil control on surface water balance explains these contrasts between the scenarios. None of the applied disturbances caused a permanent vegetation shift in the simulations. Dryland ecosystems are known to play a dominant role in the trend and variability of the global terrestrial CO2 sink. We showed that single extremely dry and wet years can have a strong impact on the productivity of drylands ecosystems, which typically lasts an order of magnitude longer than the duration of the disturbance. Therefore, this study sheds new light on potential drivers and mechanisms behind this variability.

Characterizing the Seasonal Cycle of the Northern Australian Rainy Season

AbstractIn this paper we introduce an objective definition for the onset and the retreat of the northern Australian rainy season that overlaps significantly with the Australian monsoon season. We define onset and retreat dates of the northern Australian rainy season as being the first and the last day of the year when the daily rain rate exceeds and falls below the climatological annual mean rain rate, respectively. However, our definition of onset/demise is not as restrictive as the traditional monsoon season that seeks the arrival of the westerlies and the equatorward retreat of the trough at its onset and demise, respectively. As defined in this paper, the length of the rainy season is longer than the monsoon season and includes the pre- and post-monsoon rainfall. It is noted that an early or later onset date of the northern Australian rainy season is associated with a longer or shorter, wetter or drier, and colder or warmer season, respectively. Similar relationship is also observed with demise date variations, which are, however, weaker than the onset date variations. Furthermore, we find that the relationship of the northern Australian seasonal rainfall variations with ENSO variability becomes stronger when we account for variations in the length of the rainy season compared to the fixed (December–February) monsoon season length. We also find a significant linear trend over the time period of the analysis from 1901 to 2015 toward an increasing length of the northern Australian rainy season that influences the corresponding rising trend of seasonal rainfall anomalies.

Spatio-Statistical Analysis of Rainfall and Temperature Distribution, Anomaly and Trend in Nigeria

This study aims to examine the variability of rainfall and temperature based on spatio-statistical analysis. Data for the study was gotten from the Nigerian Meteorological Agency and subjected to statistical analysis using mean, standard deviation, time series analysis, t-test and correlation. The results of the study revealed that the mean rainfall in the area is 108.6 mm, mean temperature is 28o C and mean sunshine is 4.7 hours. The result further revealed that mean onset date in the state is 13th march, mean cessation date is 10th October while the mean length of rainy season is 223 days. The result also showed that rainfall anomaly index in the area ranged between -2.12 and 2.28 while temperature anomaly ranged between -2.31 and 1.73. The correlation coefficient showed that cessation (0.408) and Length of rainy season (0.406) is significantly related to rainfall, sunshine hours (0.380) and Average temperature (0.867) is significantly related to minimum temperature, sunshine hours (-0.389) and average temperature (0.749) is significantly related to maximum temperature while onset (-0.642) and cessation (0.509) is significantly related to length of rainy season. However,there is a significant difference in onset dates, cessation dates and length of rainy season in the area. The area is experiencing a significant increase in temperature, rainfall and sunshine hours and recommends that more tress should be planted in the area and Nigerian meteorological agency should also inform farmers about the onset of the rains so as to help the farmers prepare for the planting season.
 Keywords: Climate; Rainfall; Anomaly; Temperature; Cessation; Onset
 
 Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember
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Robust late twenty-first century shift in the regional monsoons in RegCM-CORDEX simulations

We use an unprecedented ensemble of regional climate model (RCM) projections over seven regional CORDEX domains to provide, for the first time, an RCM-based global view of monsoon changes at various levels of increased greenhouse gas (GHG) forcing. All regional simulations are conducted using RegCM4 at a 25 km horizontal grid spacing using lateral and lower boundary forcing from three General Circulation Models (GCMs), which are part of the fifth phase of the Coupled Model Inter-comparison Project (CMIP5). Each simulation covers the period from 1970 through 2100 under two Representative Concentration Pathways (RCP2.6 and RCP8.5). Regional climate simulations exhibit high fidelity in capturing key characteristics of precipitation and atmospheric dynamics across monsoon regions in the historical period. In the future period, regional monsoons exhibit a spatially robust delay in the monsoon onset, an increase in seasonality, and a reduction in the rainy season length at higher levels of radiative forcing. All regions with substantial delays in the monsoon onset exhibit a decrease in pre-monsoon precipitation, indicating a strong connection between pre-monsoon drying and a shift in the monsoon onset. The weakening of latent heat driven atmospheric warming during the pre-monsoon period delays the overturning of atmospheric subsidence in the monsoon regions, which defers their transitioning into deep convective states. Monsoon changes under the RCP2.6 scenario are mostly within the baseline variability.

Projected effects of 1.5 °C and 2 °C global warming levels on the intra-seasonal rainfall characteristics over the Greater Horn of Africa

This study examines the effects of 1.5 °C and 2 °C global warming levels (GWLs) on intra-seasonal rainfall characteristics over the Greater Horn of Africa. The impacts are analysed based on the outputs of a 25-member regional multi-model ensemble from the Coordinated Regional Climate Downscaling Experiment project. The regional climate models were driven by Coupled Model Intercomparison Project Phase 5 Global Climate Models for historical and future (RCP8.5) periods. We analyse the three major seasons over the region, namely March–May, June–September, and October–December. Results indicate widespread robust changes in the mean intra-seasonal rainfall characteristics at 1.5 °C and 2 °C GWLs especially for the June–September and October–December seasons. The March–May season is projected to shift for both GWL scenarios with the season starting and ending early. During the June–September season, there is a robust indication of delayed onset, reduction in consecutive wet days and shortening of the length of rainy season over parts of the northern sector under 2 °C GWL. During the October–December season, the region is projected to have late-onset, delayed cessation, reduced consecutive wet days and a longer season over most of the equatorial region under the 2 °C GWL. These results indicate that it is crucial to limit the GWL to below 1.5 °C as the differences between the 1.5 °C and 2 °C GWLs in some cases exacerbates changes in the intra-seasonal rainfall characteristics over the Greater Horn of Africa.