Trend Analysis In Observed And Projected Precipitation And Mean .
International Journal of Current Engineering and Technology 2017 INPRESSCO , All Rights ReservedE-ISSN 2277 – 4106, P-ISSN 2347 – 5161Available at http://inpressco.com/category/ijcetResearch ArticleTrend analysis in observed and projected precipitation and meantemperature over the Black Volta Basin, West AfricaFati Aziz†* and Emmanuel Obuobie‡†Laboratoire‡Waterd’Hydrologie Appliquée, Universite D’Abomey-Calavi, Benin RepublicResearch Institute, Council for Scientific and Industrial Research (CSIR), GhanaReceived 02 May 2017, Accepted 01 July 2017, Available online 02 July 2017, Vol.7, No.4 (Aug 2017)AbstractThe study analyzed the trends in observed (1981-2010) and future projected annual precipitation and meantemperature over the Black Volta River Basin using the Mann-Kendall test and the Sen’s slope estimator. Projectedchanges in precipitation and temperature by multi-model ensemble runs over the Black Volta basin for the late(2051-2075) and end of the 21st century (2076-2100) horizons under two IPCC Representative ConcentrationPathways (RCP4.5 and RCP8.5) scenarios was also analyzed. The results showed statistically significant (at the 5%significance level) increase of 111mm in the annual rainfall over the observed period. The future direction of thistrend is uncertain as some ensemble members projected positive trends while others gave negative trends. However,both the positive and negative future trends in the rainfall were statistically non-significant. The results also showedthat the studied basin has warmed over the observed period, with significant increase of 0.9 C in the mean annualtemperature. Similarly, significant increasing trend in the mean annual temperature are projected by the ensembleruns under both RCPs for the late and end of the 21 st century. Analyses of the average annual, intra-annual andseasonal precipitation indicated high uncertainty regarding the direction of the future rainfall. Mean annualprecipitation change for the late 21 st century ranged between -16% and 6% under the RCP4.5 scenario and between-27% and 14% under the RCP8.5 scenario. The end of the 21 st century projections showed changes in meanprecipitation amounts ranging between -23% and 2% and between -33% and 13% under the RCP4.5 and RCP8.5scenarios, respectively. With regards to temperature, average annual projections by the ensemble runs showedincreases over the basin under both RCP scenarios and for both time periods. Warming over the basin is projected tobe higher under the RCP8.5 scenario than under the RCP4.5 scenario, with the end of 21st century period beingwarmer than the late 21st century. Average annual mean temperature increase across the model run ranged between2.2oC and 2.6oC under the RCP4.5 scenario and between 3.5oC and 3.7oC under the RCP8.5 scenario for the end of the21st century.Keywords: Climate change, precipitation, temperature, CORDEX West Africa, Black Volta Basin1. Introduction1 TheIPCC highlighted in their Fifth Assessment Reportthat each of the last three decades has beensuccessively warmer at the Earth’s surface than anypreceding decade since 1850 (IPCC, 2014a). Indeed,the effects of rising temperatures are being felt globallyand there is increasing pressure to put in effective andpracticable adaptation measures at the regional andlocal levels. In West Africa, for example, temperaturesare projected to increase by between 3 C and 6 C bythe end of the 21st century under a range of scenarios.Whereas rainfall projections for the region are lesscertain many global models project a wetter mainrainfall season with a slight delay in the start of the*Corresponding author’s Phone: 233244873780; ORCID ID: 00000001-5303-5918rainfall season towards the end of the 21st century(CDKN, 2014). Changes in climate are expected toincrease the pressure on water availability, affect foodsecurity and impact on human health in the region(IPCC 2013, IPCC 2014b). The Black Volta River Basinin West Africa supports economic activities such asagriculture, hydro-power generation and domesticwater supply in Burkina Faso, Cote D’lvoire and Ghana.These hydrological benefits are threatened by globalchange (Kasei, 2009). Therefore, information on thecurrent climate as well as the projected changes in thefuture can be useful for the sustainable developmentand management of water and other natural resourcesin the region.In the past, climate projections over West Africawere limited in part by the coarse resolution of GCMs(normally 100–400 km resolution) as well as the largespread among GCM projections (Hoerling et. al., 2006;1400 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
Fati Aziz and Emmanuel ObuobieTrend analysis in observed and projected precipitation and mean temperature.Giannini et al., 2008). More recently, however, theCoordinated Regional Downscaling EXperiment(CORDEX), an initiative founded by the World ClimateResearch Program of the World MeteorologicalOrganization produced an ensemble of high-resolutionhistorical and future climate projections at regionalscales (Giorgi et al. 2009; Jones et al. 2011). For theAfrica domain, the RCM simulations are at a gridresolution of 0.44 x 0.44 (approximately 50 km),which is an improvement over previous simulations forAfrica. Studies conducted over the entire Africancontinent (e.g. Nikulin et al., 2012; Panitz et al., 2014;Kim et al., 2014 and Dosio et al., 2015) and at theregional level (e.g. Klutse et al., 2014; Abiodun et al.,2015 and Endris et al., 2015) have shown that CORDEXRCMs simulate well the spatial and temporaldistributions of the West African precipitation, withsome seasonal and sub-regional biases.In this study we analyzed the trends in historical(1981-2010) annual precipitation and meantemperature over the Black Volta River Basin using theMann-Kendall test and Sen’s slope estimator. The studyalso analyzed 12 ensemble runs together with 4ensemble means of the runs generated from thecombination of 2 RCMs driven by 3 GCMs for the IPCCmedium-low (RCP4.5) and high (RCP8.5) emissionscenarios for the late 21st century (2051-2075) andend of the 21st century (2076-2100). The trends in theprojected annual precipitation and mean temperaturewere also evaluated.Average monthly minimum temperature in the basinranges between 18oC to 25oC while average maximumtemperatures range from 30oC to 37oC. Agriculturerepresents the main economic activity of the basin,with the most commonly cultivated crops (usuallyunder rain- fed conditions) being millet, sorghum,maize, groundnuts and yams (Barry et. al., 2005). TheBasin’s population was approximately 4.5 million in2000 and projected to reach 8 million by 2025 (Annor,2012). The population density ranges between 8 and123 people/km2 (Allwaters Consult, 2012), and thepopulation growth rate, around 3% per annum (GreenCross International, 2001).2. Materials and Methods2.1 Study areaThe Black Volta River Basin (BVRB) is a major subbasin of the Volta River Basin in West Africa. It islocated between Latitude 7.0 N and 14.0 N andLongitude 5.3 W and 1.3 W (Annor, 2012). The basin isshared by Ghana, Burkina Faso, Cote D’Ivoire and Mali(Figure 1) and has a total area of about 142,056 km2.The annual climate in the basin is characterized by twodistinct periods of wet or rainy season and the dryseason. Rainfall pattern in the northern half of thebasin is mono-modal with peak in August/Septemberwhile the South has a bi-modal pattern with peaks inMay/June and August/September. The mean annualrainfall varies from less than 500mm in the extremenorth of the basin in Mali to about 1,350 mm in theforested areas in south-eastern Ghana (MWH, 1998).About three-quarters of the annual rainfall occurbetween May and September (Obuobie et al., 2017).Studies in the evolution of rainfall in West Africa wherethe BVRB is located revealed that the region sufferedstrong rainfall deficit in the 1970’s following wetperiods in the 1950s and 1960s (Hubert andCarbonnel, 1987; Mahe et al., 2001; Nicholson andPalao, 1993; Nicholson, 2000). According to recentstudies (Druyan, 2011; Ibrahim et al., 2014; Sylla et al.,2016) precipitation over some parts of West Africa hasseen some recovery since the 1980s.Fig.1 Map of Black Volta Basin with Meteorologicalstations used in the study2.2 Data set and model descriptionThe data used in this study included observed (19812010) precipitation and mean temperature series foreleven climate stations (Table 1) in the BVRB obtainedfrom the Meteorological Agencies in Ghana andBurkina Faso. Model simulation data covering 19812005 (control period) and 2051-2100 (future period)for RCP 4.5 and RCP 8.5 were obtained from theCORDEX West African project. As mentioned earlier,the simulation data consisted of projections from 2RCMs driven by 3 GCMs for a total of 3RCM/GCM pairs(Table 2). The 2 RCMs, were the Rossby Centre of theSwedish Meteorological and Hydrological Institute(SMHI) regional climate model - fourth generation(RCA4) and the Regional Atmospheric Climate Model(RACMO). Simulations from these models were used as1401 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
Fati Aziz and Emmanuel ObuobieTrend analysis in observed and projected precipitation and mean temperature.they were the only data available to us at the time ofthe study. The RCA4 is based on HIRLAM, a numericalweather prediction model and is an improvement ofthe RCA3 (Samuelsson et al. 2011). It has undergonephysical and technical changes to make it applicable forany domain worldwide (Strandberg et al., 2014).Within the CORDEX project framework, the SMHIapplied the RCA4 model to (Strandberg et al., 2014)downscale the ERA-Interim Reanalysis (1980-2010)and eight (8) different GCMs from the Coupled ModelIntercomparison Project 5 (CMIP5) archives over theAfrican domain (Jones et al., 2011, Nikulin et al., 2012).The data are available for RCP 2.6, RCP4.5 and 8.5 andcover the period 1951-2100. The RegionalAtmospheric Climate Model (RACMO) is on the otherhand a hydrostatic limited-area model developed andmaintained by the modeling group at the RoyalNetherlands Meteorological Institute (KNMI) (vanMeijgaard et al., 2008). The first version of the model,RACMO1 combines the HIRLAM model with the physicsof ECHAM4. The second version, RACMO2, wasdeveloped based on the ECMWF-NWP release cy23r4and the Numerical Weather Prediction (NWP) modelHIRLAM version 5.0.6 (Lenderink et al., 2003). Climatechange simulations generated with RACMO22T model,driven by the EC-EARTH for RCP 4.5 and 8.5 within theCORDEX project are used in this study.Table 1 Climate stations used in this studyNo.1234567891011Station NameBatie (BF)Bobo-Dioulasso (BF)Bole (GH)Boromo (BF)Bui (GH)Dedougou (BF)Gaoua (BF)Hounde (BF)Lawra (GH)Wa (GH)Wenchi (GH)Latitude 7.75Longitude 2.1*BF Burkina Faso; GH GhanaTable 2 RCMs with driving GCMs from CORDEX used inthis studyRegional Climate Model(RCM)Global ClimateModel (GCM)GCM/RCMCombinationRCA4 (SMHI)(Samuelsson et al. 2011;Kupiainen et al. 2011;Strandberg et al. 2014 )MPI-ESM-LR (MPIM)(Stevens et al.2013)RCA4/MPI-ESM-LRRCA4 (SMHI)(Samuelsson et al. 2011;Kupiainen et al. 2011;Strandberg et al. 2014 )CCCma-CanESM2(Chylek et al.,2011)RCA4/CCCmaCanESM2KNMI Regional ClimateModel, (RACMO22T)(van Meijgaard et al.2008)ICHEC-EC-EARTH(Hazeleger et al.2010)RACMO22T/ICHEC-ECEARTH2.3 Trend analysis of observed and projected annualprecipitation and mean temperatureAssessment of trends in observed (1981-2010) andprojected (2051-2075 and 2076-2100) annualprecipitation and mean temperature over the basinwas carried out using the non-parametric MannKendall (MK) test (Mann, 1945; Kendall 1975; Gilbert1987). The MK test has been widely applied inanalyzing trends in climatologic and hydrologic timeseries (Mavromatis and Santhis, 2011; Karpouzos et al.,2010; Yue and Wang 2004). According to the test, anull hypothesis H0, which assumes that there is notrend in the series (the data is independent andrandomly ordered), is tested against an alternativehypothesis, H1, which assumes otherwise (Onoz andBayazit, 2012). For this study, the null hypothesis wastested at the significance level α 0.05 for both annualprecipitation and mean temperature. P-values less than0.05 indicated the existence of statistically significanttrends while P-values greater than 0.05 indicated thattrends in the series were statistically insignificant. Themagnitude (slope) of the trends were estimated usingthe Sen’s slope estimator (Sen, 1968). A briefexplanation of the procedure for the MK test and theSen’s estimator are presented in Appendix A1 and A2respectively. The trend analysis was performed at thebasin scale. The basin data on rainfall and temperaturewere obtained as averages of data from the 11 climatestations used in the study.2.4 Statistical downscaling/biasgeneration of ensemble runscorrectionandThe statistical downscaling/bias-correction of thefuture precipitation and temperature data obtainedfrom the RCMs for the eleven (11) climate stationswere done with the Quantile-Quantile (Q-Q)transformation technique (Maraun et al., 2010;Themeßl et al., 2011). Prior to its use on the futureclimate data, the Q-Q technique was adapted to eachstation using the statistics of the observed climate atthe stations. The Q-Q transformation procedure isdescribed in detail by Amadou et al., (2015) and Sarr etal., (2015). A brief description is given in Appendix A3.Twelve ensemble runs consisting of RCM/GCM outputsfor the RCP 4.5 and RCP 8.5 were generated for the two25-year periods: 2051-2075 (referred to as the late21st century or 2060s) and 2076-2100 (the end of the21st century or 2080s). Four additional scenariosbased on the ensemble mean of the RCM/GCM pairswere also generated. In total, sixteen ensemble runswere formed (Table 3) and used in the analysis.Table 3 Model scenarios used in this studyScenarioNumber123Model ScenariosRACMO22T/ICHEC-EC-EARTH (RCP4.5/2060s)RACMO22T/ICHEC-EC-EARTH (RCP4.5/2080s)RACMO22T/ICHEC-EC-EARTH (RCP8.5/2060s)1402 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
RACMO22T/ICHEC-EC-EARTH (RCP8.5/2080s)RCA4/CanESM2 (RCP4.5/2060s)RCA4/CanESM2 (RCP4.5/2080s)RCA4/CanESM2 (RCP8.5/2060s)RCA4/CanESM2 (RCP8.5/2080s)RCA4/MPI-ESM-LR (RCP4.5/2060s)RCA4/MPI-ESM-LR (RCP4.5/2080s)RCA4/MPI-ESM-LR (RCP8.5/2060s)RCA4/MPI-ESM-LR (RCP8.5/2080s)Ensemble of RCMs (RCP4.5/2060s)Ensemble of RCMs (RCP4.5/2080s)Ensemble of RCMs (RCP8.5/2060s)Ensemble of RCMs (RCP8.5/2080s)2.5 Assessment of model-uncorrected-simulation andmodel-corrected –simulation against observed climatePlots of average monthly precipitation andtemperature of the model- uncorrected and -correcteddata were made at one of the stations of the Basin(Bobo-Dioulasso) and compared with plots of theobserved data to assess the superiority of the correcteddata over the uncorrected. The comparison was also toestablish the importance of bias correction in climatechange assessment study. The assessment was done bycomparing the annual mean values, and standarddeviations of the model-uncorrected and –correcteddata to the observed data. In addition, plots of monthlyprecipitation, monthly mean temperature, andprobability of exceedence of defined precipitationclasses were made to assess the accuracy with whichthe model-uncorrected and –corrected data mimic theobserved.2.6 Estimation of changes in precipitation andtemperatureProjected changes in precipitation and meantemperature over the basin were assessed under theRCP 4.5 and RCP 8.5 scenarios using the downscaledand bias-corrected RCM runs for the late- and end ofthe 21st century. Relative changes (%) were calculatedfor precipitation while absolute changes (oC) werecomputed for the mean temperature. The changeswere determined and discussed at the annual, intraannual and seasonal time steps. Prior to analysis, thebias-corrected data from the 11 climate stations wereaveraged to obtain basin average data.3. Results and discussion3.1 Trends in observed annual precipitation andtemperatureTrend analysis of annual precipitation over the basinrevealed a statistically significant increase (Sen’s slope 3.7 mm/year, p-value 0.02;) of 111mm over the 30year period (1981-2010). The lowest annualprecipitation in the observed period was 744mm(1981) and highest, 1188mm (1991) as shown inFigure 2. Our findings of increasing precipitation in theBlack Volta is in agreement with findings of Sylla et al.(2016), which observed statistically significant positivetrends in precipitation over West Africa. Theaforementioned study noted that Burkina Faso, locatedin the northern half of our study area, is one of thecountries which experienced an increase inprecipitation during the 1983-2010 period. In a similarstudy, Maidement et al. (2015) reported statisticallysignificant increases in annual rainfall across the Sahelbetween 1983 and 2010. Other studies in the Sahel byNicholson (2005), Mahé and Paturel (2009) and morerecently Ibrahim et al. (2014) for example alsorevealed that annual precipitation in the region hasincreased since the end of the 1990s.Consistent with the IPCC report (IPCC, 2013) theanalysis of observed mean temperature over the BVRBindicated a statistically significant increase (5% level ofsignificance; p-value 0.00; Sen’s slope 0.03) of 0.9 Cover the 30-year period (0.3 C per decade). Accordingto Sylla et al. (2016), countries such as Ghana and laCote d’lvoire, both located in the BVRB, experiencedthe most significant warming signals during the 19832010 period. Figure 3 shows the increase in meantemperature over the basin for the period of analysis.Black Volta Basin: Annual Precipitation1300Precipitation (mm)45678910111213141516Trend analysis in observed and projected precipitation and mean 10------ Trend: 3.7 mm per year [p-value 0.02]Fig.2 Trend analysis of annual precipitation over theBlack Volta River Basin (1981-2010)Temperature (oC)Fati Aziz and Emmanuel ObuobieBlack Volta Basin: Mean Annual 980199020002010---- trend of 0.3 oC per decade [p-value 0.00]Fig.3 Trend analysis of mean temperature over theBlack Volta River Basin (1981-2010)1403 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
Fati Aziz and Emmanuel ObuobieTrend analysis in observed and projected precipitation and mean temperature.Table 4 Basic statistics of uncorrected and bias- corrected RCA4/ CanESM2 model simulations of historical (19812005) temperature and precipitation at 7.1280.383.2 Assessment of the model- corrected and –uncorrectedsimulations of the observed climate350Precipitation(mm)300250200150100500Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMonthsObservedCorrectedUncorrectedFig.4 RCA4/ CanESM2 bias-corrected and –uncorrected precipitation and observed data at theBobo-Dioulasso station (1981-2005)Probability of 0UNCORRECTED0.050.00Less than1mm1-10mm 11-50mm Greaterthan50mmThreshold353025Temperature (oC)Figures 4, 5 and 6 present the trends in monthlyprecipitation, the probability of exceedance ofprecipitation events and the trends in mean monthlytemperature, respectively, at the Bobo-Dioulassostation in the north of the basin in Burkina Faso. Theplots were based on station observed data as well asthe RCA4/CanESM2 model-corrected and –uncorrecteddata for the precipitation and mean temperatures. Asshown in Figure 4, both the model-corrected and–uncorrected simulations show a double peak in theprecipitation while the observed data has a single peak.However, the double peak in the corrected simulationis weak while the uncorrected exhibits a strong doublepeak.Standard DeviationObserved Corrected Uncorrected2.011.991.8790.2591.1481.5720151050Jan Feb Mar Apr May Jun Jul Aug Sep Oct NovMonthsObservedCorrectedUncorrectedFig.6 Uncorrected and bias-corrected RCA4/ CanESM2model simulated data and historical mean temperatureat the Bobo-Dioulasso station (1981-2005)In addition, the corrected simulation fairly reproducesthe monthly amounts though it shows a slight overestimation of the May and August rainfall andunderestimates that of March, June, July andSeptember through November. The uncorrectedsimulation, on the other hand, heavily over-estimatedthe precipitation in April and May and underestimatedthe amounts for July through to November. As Figure 5shows, the model corrected data overestimated theprobability of precipitation events less than 1mm whilethe uncorrected data showed an underestimation. Inaddition, the uncorrected data overestimated highlythe probability of precipitation exceedance between1mm and 10mm. Results of the mean monthlytemperature (Figure 6) shows that the corrected modeldata represents well the observed monthlytemperature at the Bobo-Dioulasso station, with slightunder- and over-estimations. The uncorrected output,on the other hand, underestimates the monthlytemperature values in January through April andoverestimates them from June through September. Themean and standard deviation of the precipitation andtemperature at the station (Table 4) also confirms thecloseness of the corrected data to the observed data,relative to the uncorrected data. As rightly pointed outby Ehret et. al. (2012), climate simulations oftenexhibit systemic deviations from the observed climate.Our results show that bias correction is without doubtimportant for climate change impact assessment.3.3 Projected changes in precipitationFig.5 Probability of exceedance of precipitationthresholds for the bias-corrected and uncorrectedRCA4/ CanESM2 model simulates of historicalprecipitation at the Bobo-Dioulasso station (19812005)The analysis of average annual precipitation over thebasin for the late- and end of the 21st century showedhigh level of uncertainties, with mixed signals ofincreases and decreases in precipitation amountsacross the models (Table 5).1404 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
Fati Aziz and Emmanuel ObuobieTrend analysis in observed and projected precipitation and mean temperature.Ave (mm)% changeAve (mm)% changeAve (mm)% change6.471091.529.21999.37-0.011126.8812.755. 8.64-27. 9.67-6.98926.12-3.74Relative to the baseline, mean annual precipitation forthe late 21st century ranged between -16% and 6%,with a mean of -2% under the RCP4.5 scenario andbetween -27% and 14%, with a mean of -1% underthe RCP8.5 scenario. The end of the 21st centuryprojection showed precipitation changes of between 23% and 2%, with a mean of -7% under the RCP4.5scenario. The high emission RCP8.5 scenario projectschanges ranging between -33% and 13%, with amean of -4%. From the results, it is established that theuncertainty in the projections increases withincreasing RCP forcing and increasing time frames.Similar observations were made by Sylla et al. (2016).Figure 7 and 8 show the projected changes in intraannual precipitation over the BVRB for the late and endof 21st century, respectively. As shown in both graphs(7a and 7b), future rainfall projections by the modelsshow high variability consistent with findings for theWest African region reported in the IPCC 5 thAssessment report (IPCC, 2013). The variability ismostly pronounced during the wet season.Precipitation amount for the month of July for exampleis projected to range between 51mm and -16mmunder the RCP 4.5 scenario and between 81mm and 30mm under the RCP8.5 scenario in the 2060s. Fromthe months of October through December however, thevariability is highly reduced, especially under theRCP4.5 scenario. The end of the 21st century rainfallprojections also shows substantial variability, in thiscase especially in the months of February throughSeptember, which reduces from October throughDecember.Changes in precipitation for the dry (JanuaryMarch) and wet (August-October) seasons arepresented in Figures 9 and 10. In the late 21 st century,the ensemble runs project a change in the range of 6% to -35% in the dry season precipitation, with amean change of 11% for the RCP4.5 scenario. Thechange in wet season precipitation is projected torange from 4% to -10%, with a mean of -3%. Underthe RCP8.5 scenario, the change in dry and wet seasonprecipitations are projected to range from 22% to 67%, with a mean of -26%, and 9% to -16%, with amean of -1%. Similarly, the dry and wet seasonprecipitations over the basin for the end of the 21stcentury are projected to range between 20% and -48%, with a mean of -11% and from -2% to -16%, witha mean of -8% for the RCP4.5 scenario. The highemission RCP8.5 scenario projections show a rate ofchange in dry season precipitation ranging from 48%and -68%, with a mean of -18% while for the wetseason the projected changes are between 16% and 23%. The high variability in the projections across themodels and the opposing change in signals areindications of uncertainty surrounding precipitationprojections in the basin. Whereas a decrease inprecipitation over the region may cause droughts,affect agriculture development and cause a decline inhydropower generation, increases in precipitation maycause floods in the CCma-CanESM2ENSEMBLEOBSERVED300Precipitation (mm)1064.121050.772001000Jan Feb Mar Apr May JunJul Aug Sep Oct Nov DecMonths(a)Precipitation (mm)999.48End-of-Century (2076-2100)RCP4.5RCP8.5% Cma-CanESM2ENSEMBLELate-Century (2051-2075)RCP4.5RCP8.5Ave (mm)RCMsBaseline (19812010) observedmean value (mm)Table 5 Projected changes in precipitation for the late and end of 21st century in the Black Volta River Basinunder RCPs 4.5 and a-CanESM2ENSEMBLEOBSERVED4002000Jan Feb Mar Apr May JunJul Aug Sep Oct Nov DecMonths(b)Fig.7 Observed and projected intra-annualprecipitation under (a) RCP4.5 and (b) RCP8.5 for the2060s (2051-2075)1405 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
Fati Aziz and Emmanuel ObuobieTrend analysis in observed and projected precipitation and mean -LRRCA4/CCCma-CanESM2ENSEMBLEOBSERVEDPrecipitation on ecMonths(b)Fig. 8 Observed and projected intra-annual precipitation under (a) RCP4.5 and (b) RCP8.5 for the 2080s (20762100)% change in seasonal precipitation200-20-40Dry period-60Wet period-80(a)1406 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
% change in seasonal precipitationFati Aziz and Emmanuel ObuobieTrend analysis in observed and projected precipitation and mean temperature.3020100-10-20-30-40-50-60-70-80Dry periodWet period(b)Fig. 9 Changes in mean seasonal precipitation for the 2060s (2051-2071) under (a) RCP4.5 and (b) RCP8.5scenarios, relative to the baseline (1981-2010)% change in sesonl precipitation6040200-20-40-60Dry period-80Wet period(a)% change in sesonl precipitation6040200-20-40-60Dry period-80Wet period(b)Fig. 10 Changes in mean seasonal precipitation for the 2080s under (a) RCP4.5 and (b) RCP8.5 scenarios, relativeto the baseline (1981-2010)1407 International Journal of Current Engineering and Technology, Vol.7, No.4 (Aug 2017)
Fati Aziz and Emmanuel ObuobieTrend analysis in observed and projected precipitation and mean temperature.Table 6 Projected changes in temperature (oC) for the late and end of 21st century in the Black Volta River Basinunder RCPs 4.5 and 8.5RCM/GCM 2010)Observed meanvaluesRCP4.5RCP8.5RCP4.5RCP8.5Tmean (oC)Tmean (oC)AveChange30.02.1Tmean (oC)AveChange30.72.8Tmean (oC)AveChange30.22.3Tmean .530.231.431.631.427.92.02.32.13.4 Projected changes in temperature2.73.02.82.22.62.33.53.73.53.5 Trends in projected annual precipitation and meantemperatureIn agreement with the IPCC (2013) report, results ofthe temperature projections for the basin (Table 6)point towards a warmer climate in the late- and end ofthe 21st century under both RCP scenarios, relative tothe baseline (1981-2005). The projected increases intemperature by the ensemble runs are significant. Themagnitude of the projected increase in meantemperature over the basin is greater in the 2080scompared to the 2060s. As expected, the increase intemperature is higher in the RCP8.5 scenario than inthe RCP4.5 scenario. The mean annual temperature for2060s is projected to rise by between 2.0oC and 2.3oCfor the RCP4.5 scenario and 2.7 oC and 3.0oC for theRCP8.5 scenario. By the end of the 21st century, largertemperature increases between 2.2oC and 2.6oC isprojected for the RCP4.5 scenario and from 3.5oC to3.7oC for the RCP8.5 scenario. These projected changesin temperature for the basin are in line with theprojected range for West Africa (Sylla et al., 2016).The Man-Kendall trend test showed increases anddecreases in future precipitation over the basin (Table7) with majority of the trends (about 67%) being in thepositive direction. The projected trend ranges from adecrease of 5.5mm/year to an increase of 3.6mm/yearfor the RCP4.5 scenario in the late century period. Forthe RCP8.5 scenario, the trend ranges from a decreaseof 2.7mm/year to an increase of 8.6mm/year. The endof the century projected trend ranges from
These hydrological benefits are threatened by global change (Kasei, 2009). Therefore, information on the current climate as well as the projected changes in the . 2.3 Trend analysis of observed and projected annual precipitation and mean temperature Assessment of trends in observed (1981-2010) and .
All Crashes - 10 Years There is a downward trend for all crashes over the last ten years. Trend line R² -0.89 The strength of the trend is expressed through the R2 value. The closer the R2 value is to 1 or -1 the stronger the trend. Positive R 2values indicate an upward trend, negative Rvalues indicate a downward trend, and zero indicates a flat trend.
Two Styles of Trading With-Trend Seeks to enter a position in alignment with the preexisting trend, or at the beginning of a new trend. Common structures are pullbacks and breakouts. Ideal entries are often around "centers". Counter Trend Looks to take positions against the current dominant trend on the trading timeframe.
falls below or moves above a higher degree trend line, either the trend is weakening . one can spot the trend change taking place on the pink and blue twin parallel line, much before the daily signal comes on, virtually giving the best entry . i
Soil QA/QC Sample PLM Trend Analysis Report (Revision 0) I for I Libby Asbestos Site, Operable Unit 4 I February 2005 I Contract No. DTRS57-99-D-00017 Task Order No. 29 . \2603-LlbbyU129lQA.QC Trend Analysis Report\Repot1\Rev 0_2 28 051QA QC Trend Analysis Repon_Rovision 0_ doc. 1 1 1 1 i 1 I I i i i i i I 1 i i tm i
ABOUT TREND MICRO Trend Micro Incorporated is a pioneer in secure content and threat management. Founded in 1988, Trend Micro provides individuals and organizations of all sizes with award-winning security software, hardware and services. With headquarters in Tokyo and operations in more than 30 countries, Trend Micro solutions are sold through
"Michael Covel's Trend Following: Essential." —Ed Seyk ota, pro!led in Market Wizards "Trend Following by Michael Covel? I'm long this book ." —Bob Spear, Mechanica "[Trend Following] did a superb job of covering the philosophy and think ing behind trend following (basically, why it work s). You might call it the Market Wizards of
Since 1996 Michael Covel has provided top of the line trend trading systems and education to thousands in 70 countries." My research firm Trend Following is pleased to announce two additional trend following systems. These are stand-alone trend following trading systems that each tackle great trend following trading from a different .
Grade 2 Indiana Academic Standards 2014 3 . READING: Literature. There are three key areas found in the Reading: Literature section for grades 6-12: Key Ideas and Textual Support, Structural Elements and Organization, and Synthesis and Connection of Ideas. By demonstrating the skills listed in each section, students should be able to meet the Learning Outcome for Reading: Literature. Learning .
