This subject area in meteorology/climatology is called "rainfall variability." Yet LRs contributed 314.9 mm and 586.3 mm while SRs contributed 438.7 mm and 479.1 mm (Table 5) translating to a total of 754 mm and 1084 mm of seasonal rainfall in in the respective station (Table 5). It has been shown that a coefficient of variation (CV) greater than 30% in rainfall data series indicates massive variability in rainfall amounts and distributional patterns [29]. Lecture Discussion:  Temporal Variability of rainfall may be used both to characterize a climate AND to deduce evidence of climatic change. Rainfall variability & change. Weibull method for estimating probabilities and method of moment (MOM) parameter estimation methods proved to be sufficient for the task, in evaluating data series homogeneity and frequency. Generally, stations in subhumid areas of Mbeere subcounty recorded more negative anomalies in rainfall amount received compared to Embu. [21]. Run-off collection and general confinement of rain-water within the crop’s rooting zone could enhance rain-water use efficiency as demonstrated by Botha et al. Geographic information systems (GIS) and modeling have become critical tools in agricultural research and natural resource management (NRM) yet their utilization in the study area is quite minimal and inadequate. [7] noted that most studies do not provide information on the much-needed character of within-season variability despite its critical influence on soil-water distribution and productivity. Variability in the number of rainy days (CV-RD) for each seasonal month was equally high in the two study stations. This region is a strategic production region, producing about 20% of the country’s maize cover. It has two components viz. Understanding spatiotemporal rainfall patterns has been directly implicated to combating extreme poverty and hunger through agricultural enhancement and natural resource management [1]. It has a population density of 82 persons per km2 with an average farm size less than 5.0 ha per household. Rescaled cumulative deviations for seasonal months and studied rainfall stations for the period between 2000 and 2013. The IPCC climate models predict, for the Maghreb countries, lower rainfall and increased aridity. There are two types (or components) of rainfall variability, areal and temporal. The variability of rainfall in both annual and seasonal scales were evaluated using coefficient of variation (CV), standardized rainfall anomaly, precipitation concentration index (PCI), and standardized precipitation index. The coefficient of variance (coefficient of variation) statistics were utilized to test the level of mean variations in LR and SR seasonal rainfall, number of rainy days (RD) and rainfall amounts (RA), and -test statistic to evaluate the significance of variation. Noticeably, Embu appeared to be receiving more near average rainfall during SRs (2002, 2003, 2007, and 2011) contrary to the trends observed in Mbeere region (especially in Kindaruma and Kiambere) (Figure 4). This region lies in the lower midlands 3, 4, and 5 (LM 3, LM 4, and LM 5), upper midlands 1, 2, 3, and 4 (UM 1, UM 2, UM 3, and UM 4), and inner lowland 5 (IL 5) [14] at an altitude of approximately 500 m to 1800 m above sea level (a.s.l) (Figure 1). More than a decade of research on the climate-conflict nexus has produced diverse results, which could imply that the link is context specific. In this study, the resultant patterns of spatial distribution for each map were an outcome of the generated patterns from the mapping of the index value (the mean annual precipitation) and as influenced by the spatial local conditions (elevation) including the nonexistence of altitudinal variability of the parameters of the distribution function and the interpolation methods used. Box 43844-00100, Nairobi, Kenya, Department of Agricultural Resource Management, Kenyatta University, P.O. These decisions can be optimized if the probability of dry-spells is computed after successful (effective) planting dates. The Kolmogorov-Smirnov (K-S value) Test values, -Square for the seasonal rainfall, and the values of the average rainfall means for rainfall months are summarized in Tables 3(a) and 3(b). Some climate models indicate that rainfall variability is likely to increase, pointing to more frequent and intense droughts. The study of the latter is important in understanding climate change. The Earth’s climate system includes the land surface, atmosphere, oceans, and ice. Generally, onset months (March and October) and cessation months (May and December) received highly variable rainfall amounts compared to mid-seasonal months. Results showed that available rainfall data series from study station are homogenous implying that the time series were a record of one population. An intrastation seasonal comparison showed that SRs in Embu were less variable but more drier compared to LR seasons. Daily primary and secondary rainfall time series were captured into MS Excel spread-sheet where seasonal rainfall totals for both Short Rains (SR) and Long Rains (LR) that is, March-April-May (MAM) and October-November-December (OND), respectively—annual average and number of rainy days were computed. The authors declare that there is no conflict of interests regarding the publication of this paper. [21] established that seasonal rainfall amount greater than 450 mm is indicative of a successful growing season and described it as a threshold rainfall amount. The degree to which rainfall amounts vary across an area or through time is an important characteristic of the climate of an area. Some of the variability does not appear to be caused systematically and occurs at random times. It is thus essential to match the crop phenology with dry-spell lengths based days after sowing to meet the crop water demands during the sensitive stages of crop growth. This paper reported rainfall variability and drought characteristics under climate change in two agro-climatic zones of southwestern Nigeria. (b) Probability of average seasonal months’ rainfall exceedance and return-periods for the LRs and SRs in Mbeere subcounty. Territoire en mouvement no 14 et 15. Frequency analyses of meteorological data require that the time series be homogenous in order to gain in-depth and representative understanding of the trends over time [17]. These account for close to 90% of total rainfall received annually; implying that smaller proportions of rainy days supplied much of the total amounts of rainfall received in the region. It would also appear that most stations in Mbeere region received more rainfall during SR season with November alone accounting for about 60% of total seasonal rainfall amount received while April accounts for 51% of the LR rainfall in the case of Machang’a. The consecutive dry days were prepared from historical data. The fluctuations comprising climate variability can influence patterns of … High rainfall variability and chances of prolonged dry-spells established in this study also demand that farmers ought to keenly select crop varieties and types that are more drought resistant (sorghum and millet) other than common maize cropping. rainfall variability translation in English-French dictionary. Many studies on rainfall variability had been used data at relatively in all resolutions, either global climate models (GCMs; e.g. Conversely, the incumbent study showed that the decade between 2000 and 2013 experienced marked increases in SRs and a decrease in LRs. This study was conducted on 27 Sahelian climatic stations in three countries (Burkina Faso, Mauritania, and Senegal). This subject area in meteorology/climatology is called "rainfall variability." During this study, the probabilities that seasonal rainfall would exceed this threshold were quite low (at most 30% for a return period of 3.33 years). Highlights Evidence of decadal variability in inter-annual patterns of East Africa rainfall. J. Mzezewa, T. Misi, and L. Ransburg, “Characterization of Rainfall at a Semi-arid Ecotope in the Limpopo Province (South Africa) and its Implications for Sustainable Crop Production,” 2013. For this study, Kriging was extended by the regional regression for each index value for areas whose terrain or other controls could have contributed to the spatial variability of the trends, explaining its better predictability. 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