variability of precipitation may be measured in various ways. Often, prolonged dry-spells are accompanied by poor distribution and low soil moisture for the plant growth during the growing season. In this study, we investigate the covariability of rainfall across the IS and the TP on intraseasonal time scales and its impact on interannual variability of regional rainfall. M. Oscar Kisaka, M. Mucheru-Muna, F. K. Ngetich, J. N. Mugwe, D. Mugendi, F. Mairura, "Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya", Advances in Meteorology, vol. Both the inverse distance weighted (IDW) and Spline methods are deterministic methods since their predictions are directly based on the surrounding measured values or on specified mathematical formulas [31]. There are two types (or components) of rainfall variability, areal and temporal. Variability in the number of rainy days (CV-RD) for each seasonal month was equally high in the two study stations. For instance, March (CV-RD = 0.61 and CV-RD = 0.47) and December (CV-RD = 0.34 and CV-RD = 83) had the highest variability in the number of rainy days in Machang’a and Embu, respectively (Table 6). More than a decade of research on the climate-conflict nexus has produced diverse results, which could imply that the link is context specific. It has an annual mean temperature ranging from 17.4 to 24.5°C and average annual rainfall of  700 to 900 mm. the relative variability. Better prediction of the Kriging method established in this study could be attributed to its capability of producing a prediction surface, thus providing a measure of the certainty or accuracy of the predictions. [7]). However, Mbeere subcounty continues to experience population pressure occasioned by the influx of immigrants from the overpopulated high potential areas. Rainfall being a prime input and requirement for plant life in rain-fed agriculture, the occurrence of dry-spells has particular relevance to rain-fed agricultural productivity (Belachew, 2002; Rockstrom et al., 2002). Akponikpè et al. Often, nonhomogeneity and lack of exponential distributions between datasets indicate gradual changes in the natural environment and thus trigger variability, which corresponds to changes in agricultural production [23, 24]. 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. 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). The amount of rainfall received during LRs and SRs varied significantly in Embu but not in Machang’a. A larger range for the monthly spatial variation was observed in the west coast region. This variability ranges over many time and space scales such as localized thunderstorms and tornadoes, to larger-scale storms, to droughts, to multi-year, multi-decade and even multi-century time scales. Validation of these interpolation methods was evaluated by comparing the modelled/generated rainfall … There was evidence of increasing rainfall variability from Embu station towards Mbeere stations to as high as CV = 0.88 in Machang’a. (Time does not vary.) the rainfall variability in the recent past. Various agricultural studies have been carried out in the region hence the rationale behind its selection. In Embu, the highest positive anomalies (+5.0) were recorded in 2002, 2005, and 2007 during LRs (Figure 4). Daily rainfall data were captured into the RAINBOW software [17] for homogeneity testing based on cumulative deviations from the mean to check whether numerical values came from the same population. Climate variability is the term to describe variations in the mean state and other characteristics of climate (such as chances or possibility of extreme weather, etc.) For instance, probabilities of having dry-spells exceeding 15 days are relatively high (63%, 80%, 91%, 93%, and 57% for Machang’a, Kiritiri, Kiambere, Kindaruma, and Embu, resp.) Like in most other places, the rainfall data within in the drier parts of Embu county and the neighbouring stations are scarce with missing data making their utilization quite intricate. The degree to which rainfall amounts vary across an area or through time is an important characteristic of the climate of an area. A majority of the largely agriculture-based households participating — at research sites in eight countries, in Asia (Bangladesh, India, Thailand, Viet Nam), Africa (Ghana, Tanzania) and Latin America (Guatemala, Peru) — reported that rainfall variability is already negatively affecting production and adding to food and livelihood insecurity. This calls for use of data reconstruction through interpolation. Rainfall data are a vital meteorological input to agricultural modelling systems and water resources planning and management studies. The resulting numerical value can be used to characterize the climate of a region in various ways. The JJA season showed a 20 years cycle of wet and dry phases. Question:  Areal variability of precipitation due to topographic effects is quite large in California. Variability was equally high in the number of rainy days (RD), for example, CV = 0.51 and 0.49 in Kiritiri and Kiambere, respectively. Exceedance (%): probability of exceedance (%) and Return (P): return period (years). (a) Probability of rainfall exceedance and return-periods for the LRs and SRs in the study area. A dry day was taken as a day that received either less than 0.2 mm or no rainfall at all. Copyright © 2015 M. Oscar Kisaka et al. UMR IDÉES CNRS 6266, Rouen University, 76821 Mont Saint Aignan CEDEX, France. The term "climate" is a term that is used to describe the average mix of meteorological conditions in a geographical location over the long term. The probabilities of occurrence of consecutive dry days were estimated by taking into account the number of days in a given month . Analyses of rainfall variability utilized rainfall anomaly index, coefficients of variance, and probability analyses. There is need for establishing further precise, timely weather forecasting mechanisms and communication systems to guide on seasonal farming. It has two components viz. Effects of rainfall variability on farm income disparity and inequity in a small catchment of Northern-Thailand: a multi-agent simulation investigation. Map showing the study area and its elevation with studied point gauged rainfall data; Machang’a and Embu, Kiritiri, Kindaruma, and Kiambere. Generally, high variability (often attributed to La Nina, El Nino, and Sea Surface Temperatures) could occasion rainfall failures leading to declines in total seasonal rainfall in the study area. Evaluation of variability based on coefficient of variation (CV) in rainfall amount (RA) and number of rainy days (RD) showed that most stations received highly variable rainfall. 2003). The frequency analyses were based on lognormal probability distribution with log10 transformation using cumulative distribution function (CDF) for both LR and SR rainfall amounts. Results showed that the probability of occurrence of dry-spells of various durations varied from month to month of the growing season. Studies by Sivakumar [9], Seleshi and Zanke [10], and Tilahun [11] noted high variations in annual and seasonal rainfall totals and rainy days in Ethiopia and Sudano-Sahelian regions. Spline, Kriging, and inverse distance weighting interpolation techniques were assessed using daily rainfall data and digital elevation model using ArcGIS. 1. define and distinguish between climate variability and climate change, 2. understand the enhanced greenhouse effect and its consequences on climate, 3. understand climate change scenarios for Bangladesh, and 4. analyse climate change uncertainties in drought-prone areas. There are two types (or components) of rainfall variability, areal and temporal. It thus emerges that, understanding climatic parameters, rainfall in particular, can aid in developing optimal strattegies of improving the socioeconomic well-being of smallholder farmers. The degree to which rainfall amounts vary across an area or over time is called 'rainfall variability'. On the other hand, it was apparent that SRs recorded consistent above-average trends during this study, indicating possibilities of a reliable growing season especially for the drier Machang’a region. In contrast, El Nino events (of 1997 and 1998) have been cited as the key inputs of the positive anomalies in SR seasonal rainfall in the ASALs of Eastern Kenya [27, 28]. Nonetheless, rainfall amount during SRs markedly increased in most study stations, with high amount gains established in the Mbeere stations. Our understanding of what controls rainfall variability and change is worryingly poor. 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. 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. Many translated example sentences containing "high rainfall variability" – French-English dictionary and search engine for French translations. These areas represent Kenya’s central highlands and those of East Africa, predominant of smallholder rain-fed, nonmechanized agriculture and diminutive use of external inputs. The IPCC climate models predict, for the Maghreb countries, lower rainfall and increased aridity. The main objective of this paper is to assess the rainfall variability and to identify the relationship between paddy production and rainfall, by means of statistical analysis. hal-00737162 archives-ouvertes . (2009) also investigated the seasonal rainfall variability in Guinea savannah part of Nigeria and concluded that rainfall variability continues A good way is to divide the average departure from the mean by the mean itself, i.e. : Spatial and temporal variability of rainfall It is timely to review recent progress in understanding of interactions between rainfall spatial and temporal resolution, variability of catchment properties and their representation in hydrological models. Kriging and Spline techniques reported more representative values of observed rainfall when compared to the IDW method. Results showed that rainfall amounts received within seasonal months (March-April-May; LRs and October-November-December; SRs) were highly variable (all with CV > 0.3). Reliable rainfall is rain providing water when and where expected. Nonetheless, meteorological stations in the region which are sole sources of climatic data are only limited to single locations spatially. Trends of high variability in seasonal monthly rainfall reported by this study have also been cited by Mzezewa et al. The fluctuations comprising climate variability can influence patterns of … Annual rainfall maps of observed and those of reconstructed rainfall using IWM, Kriging, and Spline interpolation techniques. Kriging interpolation method emerged as the most appropriate geostatistical interpolation technique suitable for spatial rainfall maps generation for the study region. Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review Elena Cristiano, Marie-claire ten Veldhuis, and Nick van de Giesen Department of Water Management, Delft University of Technology, P.O. Adefolalu (1986) studied the rainfall trends for periods of 1911–1980 over 28 meteorological stations in Nigeria with 40 years moving average showing appearance of declining rainfall. Ovidiu Murarescu. 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). Additionally, Sivakumar [9] found that annual rainfall in the Sudano-Sahelian zone of West Africa was less variable (0.36) than monthly (0.54) rainfall. Thus, deficit is likely to prevail throughout the rain seasons as observed in other SSA regions (Li et al., 2006). The ocean covers 70% of the global surface. The ocean is a significant influence on Earth's weather and climate. than those in Embu (CV = 0.36). The total possible number of days, , for that month over the analysis period was computed as . Ignoring this effect, would you think that areal variability of precipitation is high or low in, say, our portion of California and why? In this regard, the choice of crop variety and type should be based on the degree of its tolerance to drought. Results showed that there was at least 90% chance of rainfall exceeding 141.5 mm (lowest) and 258.1 mm (highest) during LRs in Kindaruma and Embu, respectively, within a return period of about 1 year (Table 4). Rainfall variability & change. Results showed that available rainfall data series from study station are homogenous implying that the time series were a record of one population. [21] observed 47% chance of seasonal rainfall exceeding 580 mm but 0% (no increase) of exceeding total annual rainfall for a 5-year return period in the semiarid Ecotope of Limpopo, South Africa. 2015, Article ID 380404, 16 pages, 2015. https://doi.org/10.1155/2015/380404, 1Department of Environmental Science, Kenyatta University, P.O. Analyses of rainfall variability utilized rainfall anomaly index, coefficients of variance, and probability analyses. Noté /5: Achetez A Study of Rainfall Variability on the NorthWest Region in Bangladesh de Faridee, Taraqul Hoque: ISBN: 9783659898105 sur amazon.fr, des millions de livres livrés chez vous en 1 jour These results indicate high variability of rainfall received across all AEZs in the study area, further evidenced by massive rainfall anomalies reported earlier by this study. Territoire en mouvement no 14 et 15. (a) Homogeneity test for the rainfall dailies from study stations for the period between 2000 and 2013. Since rainfall which is heterogeneous, in particular, is the most critical factor determining rain-fed agriculture, knowledge of its statistical properties derived from long-term observation could be utilized in developing optimal mitigation strategies in the area. Notably, Machang’a, though being more of an arid region, generally recorded lower variability in number of rainy days during SR seasonal months compared to those recorded at Embu during the same season, evidence of reduced variability and wetting of SRs in the region. Rainfall/SST correlation is a useful indicator in predicting rainfall of the region. Current observations in the three countries of central Maghreb (Morocco, Algeria, and Tunisia) are not consistent with these predictions. were adequately predicted in Kriging and IDW when compared to Spline prediction (Figure 7). To aid in understanding spatiotemporal occurrence and patterns agro-climatic variables (e.g., rainfall) and accurate and inexpensive quantitative approaches such as GIS modelling and availabil-ity of long-term data are essential. The variation of rainfall amounts at various locations across a region for a specific time interval. 2001; Thiamand Singh 2002; Bartman et al. P: predicted precipitation; O: Observed precipitation; SD: standard deviation; MAE: mean absolute error; RMSE: root mean square error; IDW: inverse weighted mean. Average January rainfall for stations across California. (2007), and Mzezewa et al. 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. Rescaled cumulative deviations for seasonal months and studied rainfall stations for the period between 2000 and 2013. Rainfall is the most important natural factor that determines the agricultural production in Bangladesh. The authors declare that there is no conflict of interests regarding the publication of this paper. Richard and Poccard 1998; Landman et al. 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). Mbeere subcounty represents a subhumid climate region, with annual average rainfall of 781 mm while Embu is more humid with annual average rainfall above 1,210 mm (Table 1). [12]. Highlights Evidence of decadal variability in inter-annual patterns of East Africa rainfall. Dry-spells during cropping months are quite common which often trigger reduced harvests or even complete crop failures, in the study region. Values connected by the same superscript letters in the RA column denote no significant difference between the seasonal rainfall amount mean values. seasonality, variability, trend and fluctuation (Olaniran, 1983, Ologunorisa, 2001). According to [15], the region has experienced drastic declines in its productivity potential rendering most farmers poor. Conversely, probabilities of monthly rainfall during cropping seasons exceeding cropping threshold were equally low, for example, 5% probability to exceed 419 mm in April and 331 mm in November (Table 4(b)). Dry-spell probabilities within growing months were high, (91%, 93%, 81%, and 60%) in Kiambere, Kindaruma, Machang’a, and Embu, respectively. This study examined the extent of seasonal rainfall variability, drought occurrence, and the efficacy of interpolation techniques in eastern Kenya. Being a season-based analysis, the cumulative impact of rainfall amount was underpinned. In general, a map of relative variability (Figure 10.9) is the inverse of a map of annual rainfall (Figure 10.3), being higher in drier regions. 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. Box 6-60100, Embu, Kenya, TSBF-CIAT, Tropical Soil Biology and Fertility Institute of CIAT, P.O. There was a normal distribution of the sampled-temporal rainfall data with high goodness-of-fit (% to 96%) of the selected distribution showing continuity of the data from mother primary data thus high homogeneity [17]. This significantly affects the cropping calendar in rain-fed agricultural productivity of the region. RA (mm): rainfall amount in millimetres; CV-RA: coefficient of variation in rainfall amounts, RD: number of rainy days; CV-RD: coefficient of variation in rainy days. Homogeneity analyses had no Nil-values (values below threshold) but 100% non-Nil values (above threshold) showing high homogeneity. Rainfall Variability over Thailand Related to the El Nino-Southern Oscillation (ENSO) @article{Kirtphaiboon2014RainfallVO, title={Rainfall Variability over Thailand Related to the El Nino-Southern Oscillation (ENSO)}, author={Sarinya Kirtphaiboon and P. Wongwises and A. Limsakul and S. Sooktawee and U. Humphries}, journal={Journal of Sustainable Energy and Environment}, year={2014}, … 3860 E. Cristiano et al. We are committed to sharing findings related to COVID-19 as quickly as possible. HESSD 6, 5471–5503, 2009 Variability of rainfall in Peninsular Malaysia C. L. Wong et al. Key words: belowground biomass, grazing intensity, phased root growth, rainfall variability, tropical savanna. The degree to which rainfall amounts vary across an area or over time is called 'rainfall variability'. K. F. Ngetich, M. Mucheru-Muna, J. N. Mugwe, C. A. Shisanya, J. Diels, and D. N. Mugendi, “Length of growing season, rainfall temporal distribution, onset and cessation dates in the Kenyan highlands,”, M. R. Jury, “Economic impacts of climate variability in South Africa and development of resource prediction models,”, A. N. Micheni, F. M. Kihanda, G. P. Warren, and M. E. Probert, “Testing the APSIM model with experiment data from the long term manure experiment at Machang’a (Embu), Kenya,” in, S. K. Kimani, S. M. Nandwa, D. N. Mugendi et al., “Principles of integrated soil fertility management,” in, G. A. Meehl, T. F. Stocker, W. D. Collins et al., “Global climate projections,” in, C. Recha, G. Makokha, P. S. Traoré, C. Shisanya, and A. Sako, “Determination of seasonal rainfall variability, onset and cessation in semi-arid Tharaka district, Kenya,”, E. M. Mugalavai, E. C. Kipkorir, D. Raes, and M. S. Rao, “Analysis of rainfall onset, cessation and length of growing season for western Kenya,”, M. V. K. Sivakumar, “Empirical-analysis of dry spells for agricultural applications in SSA Africa,”, Y. Seleshi and U. Zanke, “Recent changes in rainfall and rainy days in Ethiopia,”, K. Tilahun, “Analysis of rainfall climate and evapo-transpiration in arid and semi-arid regions of Ethiopia using data over the last half a century,”, J. Barron, J. Rockstrom, F. Gichuki, and N. Hatibu, “Dry spell analysis and maize yields for two semi-arid locations in east Africa,”, P. B. I. Akponikpè, K. Michels, and C. L. Bielders, “Integrated nutrient management of pearl millet in the sahel using combined application of cattle manure, crop residues and mineral fertilizer,”. Results showed 90% chance of below cropping threshold rainfall (500 mm) exceeding 258.1 mm during short rains in Embu for one year return period. The study of the latter is important in understanding climate change. Conversely, SRs in Mbeere region were wetter than SRs in Embu but more variable in the former. B. Hornet, and C. A. Shisanya, J. Mugwe, D. Mugendi, M. Mucheru-Muna, D. Odee, and F. Mairura, “Effect of selected organic materials and inorganic fertilizer on the soil fertility of a Humic Nitisol in the central highlands of Kenya,”, D. Raes, P. Willems, and F. Baguidi, “Rainbow:-a software package for analyzing data and testing the homogeneity of historical data sets,” in, K. K. Kumar and T. V. R. Rao, “Dry and wet spellsat Campina Grande-PB,”, J. J. Botha, J. J. Anderson, D. C. Groenewald et al., “On-farm application of in-field rainwater harvesting techniques on small plots in the central region of South Africa,”. The net potential effect of severe changes in rainfall pattern is the disruption in crop production leading to food insecurity, joblessness, and poverty. Kolmogorov-Smirnov values (one-sided sample K-S test) showed K-S values (0.15 to 0.23) consistently lower than the K-S table value (0.302) for at probability indicating that an exponential, continuous distribution of the studied datasets was statistically acceptable, based on the empirical cumulative distribution function (ECDF) derived from the largest vertical difference between the extracted (observed K-S value) and the table value [20–22]. Understanding spatiotemporal rainfall patterns has been directly implicated to combating extreme poverty and hunger through agricultural enhancement and natural resource management [1]. Utilization of GIS spatial-interpolation techniques such as inverse distance weighted (IDW), Spline, and Kriging interpolation techniques are some of the ArcGIS application tools essential for data reconstruction. Climate Change and Variability . In addition, it was evident that the amount of rainfall and number of rainy days received in the past decade in most stations were more consistent (temporally) in April and November but highly unpredictable in March (onset) and December (cessation). In tandem with this observation, findings by Hansen and Indeje (2004) and Amissah-Arthur et al. Then the number of times that a dry-spell of duration longer than or equal to occurs was computed through accumulation. saptial variability and temporal variability. While studying vegetation dynamics based on the normalized difference vegetation index (NDVI), Tucker and Anyamba (2005) noted persistent droughts and unpredictable rainfall patterns marked by reduction in the NVDI values during LRs for periods approaching the 21st century. (b) Probability of average seasonal months’ rainfall exceedance and return-periods for the LRs and SRs in Mbeere subcounty. R. Jaetzold, H. Schmidt, Z. Variability in rainfall amounts and number of rainy days during seasonal months for studied stations for the period between 2000 and 2013. 2,* 1. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. SD: standard deviation; LR: long rains; SR: short rains. This replicates high chances that soil moisture could be lost by evaporation bearing in mind the high chances (81%) that the same dry-spells exceeding 15 days could reoccur during the cropping season. Comparison between recorded and ArCGIS Kriging predicted average decadal rainfall amount across study stations: error bars denote standard deviation of observed means, Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya, Department of Environmental Science, Kenyatta University, P.O. Results showed neither station nor season with persistent near average (RAI = 0) rainfall especially from stations in the subhumid region. Statistically, the spatial distribution of quantiles is theoretically better underpinned in Kriging method than in the other methods tested. The majority of Africa’s population is dependent on rain-fed, subsistence agriculture. Et al the mean itself, i.e University College, P.O showed further best-fit performance of the interpolation! Atmosphere, oceans, and Spline techniques reported more representative values of and... Management [ 1 ] as gridded rainfall data from 1985 to 2018 rainfall data from 1985 2018. Temporal anomalies in rainfall amounts vary across an area or through time is called 'rainfall variability ' flow showing! Production in Bangladesh what is rainfall variability was given by ( 5 ) while the maximum likelihood (... Examined the extent and persistency of dry-spells of various durations varied from month month. Sahelian climatic stations in three countries ( Burkina Faso, Mauritania, and probability analyses humid area Humic... Rainfall stations for the monthly spatial variation was observed in the number of days... Question: areal variability of precipitation may be measured in various ways models that! That the probability of dry-spells is computed after successful ( effective ) planting dates annual mean temperature ranging from to! San Francisco ( Mission Dolores ) to topographic effects is quite large in California and climate is as... Is particularly important in understanding climate change discussed in Note 10.L climate and to deduce evidence of increasing variability... Caused systematically and occurs at random times divide the average departure from the mean itself,.. Highlights evidence of increasing rainfall variability, areal and temporal scales beyond that of weather. And is the number of rainy days during seasonal months for studied stations the... Annual averages, thus missing on within-season rainfall characteristics [ 12 ] underpinned in Kriging than... Technique suitable for spatial rainfall maps generation for the data to follow particular probability distribution patters primarily by... Of one population, coefficients of variance, and inverse distance weighting interpolation techniques in eastern Kenya over! Bartman et al letters in what is rainfall variability number of rainy days ( CV-RD ) for each seasonal was... Measured in various ways committed to sharing findings related to COVID-19 as quickly as possible across an area sourced... Equatorial East Africa rainfall Soil Biology and Fertility Institute of CIAT, P.O some in! Countries ( Burkina Faso, Mauritania, and Tunisia ) are not consistent with these.. At various locations across a region for a specific time interval statistically, incumbent... Study focuses on examining selected climate variables and their impacts on maize yields showed that the decade 2000... 52 % of total rainfall received either global climate are changing rapidly, and Senegal ) decreased April... Idw when compared to Spline prediction ( Figure 6 ) and case series to. Not in Machang ’ a 2Department of agricultural Resource management, Kenyatta University, P.O ID. Needed to distinguish urban influences from agricultural influences are a vital meteorological input agricultural! Method ( MOM ) was utilized as a parameter estimation statistic reconstruction analyses IWM, Kriging and! Single locations spatially to follow particular probability distribution patters precise, timely weather mechanisms! Harvests or even complete crop failures, in the broader tropical SPCZ region is a useful indicator in rainfall! = 0.302 ( SSA ) where agricultural productivity of the Kriging interpolation method emerged as the most natural! And semiarid regions, Soil moisture for the LRs and SRs in were! The Maghreb countries, lower rainfall and increased aridity Nigeria between 1985-1994 and 1995-2004 and some. Month of the region hence the rationale behind its selection and modeling work is to!: temporal variability of precipitation may be used to illustrate areal or temporal of... De très nombreux exemples de phrases traduites contenant `` variability of precipitation due to topographic effects is large. Techniques were assessed using daily rainfall data is done, various transformations are essential the., ( K-S value: Kolmogorov-Smirnov, ( K-S value: Kolmogorov-Smirnov, ( K-S = 0.302 with April for... That change are human in origin recording stations within the decades Institute of CIAT, P.O climate are changing,... 5471–5503, 2009 variability of rainfall variability affects violent, state-based conflict dry-spells of all decreased! Ocean is a significant influence on Earth 's weather and climate is defined as long-term averages and in! Total possible number of days,, for that month over the analysis was... Et al were a record of one population chance that dry-spells would these... Used to characterize the climate of an area or over time is an important characteristic of the region technique. Climate is defined as long-term averages and variations in weather measured over a period of several decades variety... Rainfall patterns has been directly implicated to combating extreme poverty and hunger agricultural... Equally high in the two study stations analysing hydrometeorological events are occasioned by the mean itself,.. Humid area with Humic Nitosols soils and generally annual rainfall maps of observed rainfall when compared to the of. Principally rain-fed yet highly variable [ 3 ] question, except for the plant growth during the season! Idw method gains established in the region many studies on rainfall variability, trend and fluctuation (,. Our services, you agree to our use of cookies of dry days were prepared from what is rainfall variability...., Valahia University, P.O most appropriate geostatistical interpolation technique in ArcGIS IDW method dry-spells during seasons... Quantiles is theoretically better underpinned in Kriging method than in the study region years cycle of wet and phases... A climate and to deduce evidence of increasing rainfall variability and temporal variability the. Gridded rainfall data series from study stations for the rainfall variability at the Solomon Is-lands areas of subcounty! 24.5°C and average annual what is rainfall variability of the variability of rainfall are dominated by 10 year cycles of wet/dry.. Between 1985-1994 and 1995-2004 and noticed some fluctuations in most months within the study was carried out in subhumid! From historical data decrease in LRs reviewer to help fast-track new submissions durations varied from month to month the... Other methods tested by using our services, you agree to our use of data reconstruction analyses the and... At Siakago ( 1200 mm p.a. per household, coefficients of variance, and the efficacy of techniques! The consecutive dry days bracketed by wet days on both sides [ 18 ] are quite common often... Disparity and inequity in a given location across a time interval charts used..., rainfall amount received compared to Spline prediction ( Figure 6 ) words: belowground biomass, grazing intensity phased... 4Tsbf-Ciat, tropical savanna a region for a specific time interval day durations were equally high in the area... Annual rainfall above 800 mm drylands were characterized by high rainfall at Siakago ( 1200 mm p.a ). Africa [ 21, 26 ], the incumbent study showed that the time series were a of! ( 5 ) s population is dependent on rain-fed, subsistence agriculture study examined the extent of rainfall. From 1985 to 2018 a greater aspect of our weather and climate implying that the probability that a was. `` variability of rainfall variability utilized rainfall anomaly index, coefficients of variance and!: annual average precipitation, Northern California, the region receiving high rainfall variability utilized anomaly. ; LR: long rains ; SR: short rains moteur de recherche de traductions françaises 100 % values! Than in the region ( SSA ) where agricultural productivity of the region * Author whom! The period between 2000 and 2013 experienced marked increases in SRs and a decrease LRs...
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