Techniques and Skills of Indigenous Weather and Seasonal ...



Techniques and Skills of Indigenous Weather and Seasonal Climate Forecast in Northern GhanaSupplementary materialFigure S1: The sum of accumulated observed rainfall per annum and month in the communities against GMET for the period of study (April – October 2017).Figure S2: Reliability and Usability of indicators for low, medium and high Rain forecast. Table S1: Explaining and agreeing to key meteorological terms.Type of rainfallAgreed explanationsNo Rain (0 mm/day)When rain does not fall at allLow: (0.1 -18.8 mm/day) From drizzling to rains that does not wet the soil to capacityMedium: (18.9 -36.7 mm/day)Rains that wet the soil to capacityHigh: ( > 36.8 mm/day)Rains that gathers water in farms and sometimes makes crops failAbove normal When the season will have more rains than often observed and get very wet than normal (mostly with more yield)Below normalWhen the season have less rains than observed get very dry than normal(mostly with low yield)Near Normal When the season will be just as it often is with normal experienced (mostly normal yield) OnsetWhen the rain start (When you will start planting)CessationWhen the rain will end ( Often harvesting start)Table S2: Frequency of low, medium and high rain days recorded by farmers and GMETCommunity / StationLow rainy DaysMedium rainy DaysHigh rainy DaysTotal rainy DaysGbugli1617336Yipeligu1913436Wuba514625Kushibo1491740Gbulun021921Saakuba253230Kpalsogu1019837Voggu1214531Kukuo1122841Dalun1513230Zangbalun399149Tibung67922Average of farmers1412733Tamale (GMET)[ >0.1 mm/day]5311367Tamale (GMET)[ >1 mm /day]4211357Table S3: Performance of Farmers and GMET in Rainfall Weather Forecast Community / Stationsforecast/observationTotal observe (n=214)HitMissFalse AlarmCorrect RejectionMonthly Hit performanceYes rain/Yes RainNo rain/Yes RainYes rain/No RainNo rain/No RainYes RainNo RainSeven months Hit Performance (%)April(%)May(%)June(%)July(%)August(%)September(%)October(%)Kushibo83238136401742002542142500Gbulun51638155211932400202010020100Saakuba822571273018427003317033100Kpalsogu829431343717722250142560200Voggu82343140311832600293333067Kukuo10314113241173243360676702933Dalun13175912530184433325835002950Zangbalun301954111491656160675544757567Tibung6165014222192270254043000Gbugli171944134361784775403863334033Yipelgu927481303617825033401133067Wuba42134155251891633020200033Average Community (%)?3022234034302146GMET(Tamale) at ( >0.1 mm/day)234435112671473433201346565620 Table S4: Performance of GMET Rainfall Weather Forecast Within the communities (GMET forecast against community observation)Community GMET forecast/ farmer observationTotal observe (n=214)HitMissFalse AlarmCorrect RejectionYes rain / Yes RainNo rain / Yes RainYes rain / No RainNo rain / No RainYes RainNo RainHit Performance (%)Kushibo931491254017423Gbulun1110471462119352Saakuba1218461383018440Kpalsogu1522431343717741Voggu1120471363118335Kukuo1130471264117327Dalun723511333018423Zangbalun1534431224916531Tibun616521402219227Gbugli1125471313617831Yipelgu1125471313617831Wuba718511382518928Average Performance (%)?????32Table S5: Agreement and disagreement of Farmers and GMET rainfall weather forecast ?CommunitiesAgreedisagree?Both hitboth missboth false alarmboth correct rejectionGMET hit, farmer missGMET miss, Farmer hitGMET false alarm, farmer correct rejectionGMET correct rejection, Farmer false alarmTotal Kushibo1122499873726214Gbulun3108118823728214Saakuba4151496843142214Kpalsogu49181001143434214Voggu31115104853632214Kukuo6717935134033214Dalun31613904103543214Zangbalun91713856212637214Tibun01410104663836214Gbugli51013976123734214Yipelgu2141897973334214Wuba21016114524124214Average31215100783534214Hit: Both Forecast Yes Rain and observed Yes Rain. Miss: Both Forecast Yes Rain and observed No Rain. False Alarm: Both Forecast Yes Rain and observed No Rain. Correct Rejection: Both Forecast No Rain and observed No Rain.Table S6: Farmers ability to detect low, medium and high Rain Forecast signal communityForecast/ObservationHitMissFalse AlarmCRTotal observedPerformance (%)L/LM/MH/HN/LN/MN/HL/ML/HL/NM/LM/HM/NH/LH/MH/NN/NLMHNLMHKushibo201118131324005109136149171741406Gbulun-12-1150216-012-0101550219193-5011Saakuba3011921003130130113127253218412050Kpalsogu4006167201901130111134101981774000Voggu3209104212502016001401214518325140Kukuo36-7114114233017---133112281732727-Dalun6006101213410142111125151321844000Zangbalun8301630302014132102111399116521330Tibun010646213502140011426791920140Gbugli14097360245017003134161731786240Yipelgu11016834131201500213019134178580Wuba03041160081016001015551461890210Average performance (%)????????????????????17166L=Low Rain, M =medium Rain, H=High Rain, N = No Rain, CR=Correct Rejection, - = such forecast was not made, 0 = no count Table S7: Certainty of using indicators for Yes/No Rain Forecast (Sure =high certainty, so sure= higher certainty, Very sure = Highest Certainty)IndicatorsHitMiss??Yes/Yes RainYes/No Rain Total number of times used?sureSo sureVery suresureSo sureVery sure?Sun0(0%)4(13%)0(0%)14(47%)11(37%)1(3%)30Ant6(11%)1(2%)2(4%)23(42%)17(31%)6(11%)55Bird Sound5(17%)2(7%)2(7%)9(31%)5(17%)6(21%)29Butterflies1(9%)4(36%)0(0%)4(36)1(9%)1(9%)11Caterpillars1(8%)3(23%)0(0%)1(8%)5(38%)3(23%)13Clouds3(3%)13(11%)4(3%)44(37%)38(32%)16(14%)118Cow1(6%)1(6%)0(0%)7(44%)6(38%)1(6%)16Duck1(6%)2(13%)0(0%)1(6%)10(63%)2(13%)16Earthworm1(2%)6(12%)2(4%)7(14%)24(47)11(22%)51Fog3(6%)4(8%)0(0%)13(27%)23(48%)5(10%)48Frog2(11%)1(6%)0(0%)6(33%)7(39%)2(11%)18Hot Weather10(8%)18(14%)1(1%)51(38%)39(29%)14(11%)133Moon3(8%)5(14%)1(3%)14(39%12(33%)1(3%)36Mosquitoes4(14%)5(18)1(4%)10(36%)4(14%)4(14%)28Soil1(8%)0(0%)0(0%)3(23%)7(54%)2(15%)13Wind2(4%)5(9%)2(4%)20(36%)22(40)4(7%)55Table S8: Certainty of using indicators for low, medium and high Rain forecast (Sure =high certainty, so sure= higher certainty, Very sure = Highest Certainty)?Forecast??High RainLow RainMedium RainSo sureVery suresureSo sureVery suresureSo sureVery suresureObservedHigh Rain?Sun000100000Ant000001000Bird Sound000101000Butterflies000100000caterpillars000001000clouds010100110earthworm001000000Hot Weather000002000Moon010101100Mosquitoes000101000Wind100000000Low Rain?Sun00010200Ant000113?10Bird Sound01002110Butterflies000200100caterpillars100100100clouds010201400cow000000100Duck000001100earthworm000100200fog000202001Frog000001100Hot Weather000410800Moon100100001Mosquitoes000002101Wind000010100Medium Rain?Ant000002020Bird Sound000002130Butterflies000001010clouds200001013cow000000000Duck000000001earthworm010000003fog000000002Frog000001010Hot Weather0005060111Moon000101020Mosquitoes00010?012soil000001010Wind000112042No Rain?Sun1022190128Ant012124190355Bird Sound11?325?101Butterflies11000303Caterpillars200120032Clouds1067652603722Cow100314082Duck220301045Earthworm3322320719Fog2211021212511Frog000315094Hot Weather2212694428111Moon313305196Mosquitoes0113350111Soil110313073Wind500101150267Table S9: Farmers and GMET 2017 seasonal forecast against observation in each communityCommunitiesTotal Rainfall amount forecastIndicators UseTotal Rainfall ObservedOnset ForecastIndicators UsedOnset ObservedCessation ForecastIndicators UsedCessation ObservedKushiboabove normallarge number of migrating butterflies15632nd Week Aprillarge flocks of swallow birds migrating with loud sound 4th week April1st Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberGbulunNear NormalHotness of the weather over the dry season has been moderate12433rd Week AprilThe flowering of Baobab tree and emergence of new leaves3rd week April2nd Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberSaakubaNear Normal?Normal appearance of the sun4924th Week AprilHotness of the weather/ temperature 2nd week may4th Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberKpalsoguabove normal1. Large number of Hornbils with loud singing noise 2. Frequently occurring wind swirling at a high frequency 9824th Week AprilRapid increase in anthills 4th week April2nd Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberVogguNear NormalSaw crows flying in groups879?3rd Week Aprilappearance of large number of migrating butterflies 3rd week April1st Week OctoberNo clear sign. Used previous experience1st Week OctoberKukuoNear NormalOnly few Woolly bears Caterpillars have emerged12432nd Week Aprilswirling wind at a high frequency 2nd week April3rd Week OctoberNo clear sign. Used previous experience and total rain forecast2nd Week OctoberDalunBelow normalbirds built nest close to dam 519.53rd Week AprilRapid increase in anthills 1st week April1st Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberZangbalunabove normalflowering of Baobab tree and leaves emergence moon are covered by cloudlike appearance 6063rd Week AprilHearing an owl hooting in the evening is an indication of the rain onset1st week April4th Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberTibunNear NormalNormal appearance of the sun5874th Week AprilHigh temperature that leads to profuse sweating 1st week of June1st Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberGbugliNear NormalSaw crows flying in groups8622nd Week AprilBurning heat from the high temperatures 1st week April4th Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberYipelguabove normalmoon are covered by cloudlike appearance 7743rd Week Aprillarge number of migrating butterflies4th week April3rd Week OctoberNo clear sign. Used previous experience and total rain forecast3rd Week OctoberWubaNear NormalThe number of migrating butterflies is normal 7843rd Week AprilBurning heat from the high temperatures 2nd week may1st Week OctoberNo clear sign. Used previous experience and total rain forecast1st Week OctoberGMET(Tamale)Near Normalforecast model simulations and statistical estimation results741.84th week April- 1st week of Mayforecast model simulations and statistical estimation results4th week AprilEnd of Octoberforecast model simulations and statistical estimation 1st Week October8936186639AB00ABFigure S3: Communal mental model of degree of influence of IEIs used for weather (A) and seasonal climate (B) forecast. The matrix of these relationships are in Table S12 of supplementary material, Participants assign probability of 0.25 (low), 0.5(medium) and 1 (high) for each IEI. The probability is depicted by the thickness of the arrow (the bigger the arrow the higher the probability).Table S10: Summarised matrix of the communal mental model of degree of influence of IEIs used for weather and seasonal climate forecast. Participants assign probability of 0.25 (L=low), 0.5(M=medium) and 1 (H=high) for each IEI. “ –“ means no relationship. A,B and C represent Above, below and normal rainfall WEATHERSEASONAL CLIMATEIndicatorsLow RainMedium RainHigh RainIEIOnsetABNCessationCloudsLMHBirdsHHMH-MosquitoesLMHFrogHH---Hot WeatherLHHDogsHH---CowMHLHot WeatherH----ButterfliesLMHAntsHHLMHMoonLMMMoonHHLM-FrogLMHStars---HCaterpillarsLLHBaobab TreeHHLM-DuckMHHCowsH---FogHMLDuckH----SoilMMLReptilesH----BirdsMHHWindHHLM-AntMMHSun-HLM-EarthwormMHHCloudsH----SunLHMLighteningH----WindLMMMosquitoesH----ButterfliesHHLM-CaterpillarsHHLH-Table S11: Descriptive statistics of IEIs used StatisticsValueMean42.375Standard Error9.202298173Median30.5Mode55Standard Deviation36.80919269Sample Variance1354.916667Kurtosis2.630349998Skewness1.749922916Range126Minimum11Maximum137Sum678Count16Confidence Level (95.0%)19.61423426lower bound 22.76076574upper bound61.98923426Table S12: Schematic contingency table for deterministic forecasts of a sequence of n binary events. The numbers of observations/forecasts in each category are represented by a, b, c and d.Event forecast Event observedYes NoTotalYes a (Hits) b (False alarms) a + bNoc (Misses)d (Correct rejections)c + dTotal a + c b + d a+ b + c + d = n ................
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