Comparison of CGCM3, CSIRO MK3 and HADCM3 Models in Estimating the Effects of Climate Change on. Temperature and Precipitation in Taleghan Basin

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1 America Joural of Evirometal Protectio, 2018, Vol. 6, No. 1, Available olie at Sciece ad Educatio Publishig DOI: /ev Compariso of CGCM3, CSIRO MK3 ad HADCM3 Models i Estimatig the Effects of Climate Chage o Temperature ad Precipitatio i Talegha Basi Arash YoosefDoost 1,*, Hossei Asghari 2, Reza Abuuri 1, Mohammad Sadegh Sadeghia 1 1 Civil Egieerig Departmet, Islamic Azad Uiversity Cetral Tehra Brach, Tehra, Ira 2 Eviromet Departmet, Uiversity of Tehra, Tehra, Ira *Correspodig author: YoosefDoost@Gmail.com Abstract Climate chage is a sigificat chage i weather or i its variability i a log period. This chage could be i the average of temperature, raifall, humidity, weather patters, wid, ad sulight ad so o. Atmosphere-Ocea Geeral Circulatio Model (AOGCMs) have bee developed to simulate curret climate of the plaet ad are able to predict future climate chage of the Earth. I this paper the performace of CGCM3, CSIRO Mk3 ad HadCM3 models i estimatig the effects of climate chage o temperature ad precipitatio of the Talegha basi were studied. The results show that despite relatively acceptable performace of all three models i temperature modelig, it seems that the outputs of HadCM3 model for this basi are more desirable whe compared with CGCM3 ad CSIRO MK3 models ad it is ca be said that HadCM3 seems to be more reliable for this basi. Keywords: Climate Chage, Atmosphere-Ocea Geeral Circulatio Model, AOGCM, CGCM3, CSIRO Mk3, HadCM3 Cite This Article: Arash YoosefDoost, Hossei Asghari, Reza Abuuri, ad Mohammad Sadegh Sadeghia, Compariso of CGCM3, CSIRO MK3 ad HADCM3 Models i Estimatig the Effects of Climate Chage o Temperature ad Precipitatio i Talegha Basi. America Joural of Evirometal Protectio, vol. 6, o. 1 (2018): doi: /ev Itroductio Climate chage is irreversible chage i the average of weather coditios which occurs i a regio. I other word, statistically sigificat chages i the average of weather coditios or its variability that cotiues over a log period. This chage could be i the average of temperature, raifall, humidity, weather patters, wid, ad sulight. Climate could be warmer or colder ad the average of values i each factor ca icrease or decrease over time. Some researchers cosider the icrease of greehouse gases as the most importat factor for gradual rise i global ad oceaic temperatures. Global warmig of the Earth has caused two importat pheomea which are icrease of global mea temperature ad cosequetly a icrease i sea level i the last hudred years. I additio i regioal ad local scales, climate chage has had a cosiderable ifluece o precipitatio, evaporatio, surface ruoff ad extreme weather evets. Idustries ad factories growth from the begiig of idustrial revolutio ad cosequetly, fossil fuels cosumptio beside the destructio of forests ad grasslads ad chage of agricultural lads usage are results of huma activities ad have icreased the cocetratio of greehouse gases particularly CO 2 from 280 ppm i 1750 to 379 ppm i Studies show that if curret tred i use of fossil fuels cotiues, the cocetratio of CO 2 could reach more tha 600 ppm by the ed of the twety-first cetury [1]. Accordig to the Itergovermetal report about Climate Chage, the Earth's surface temperature has icreased 0.3 to 0.6 degrees Celsius because of greehouse gas emissios over the past cetury ad it is predicted that its amout will rise to 1 to 3 C util Climate chage is a complex Atmospheric- oceaic ad the log-term pheomeo that ca be iflueced by atural factors such as volcaoes, solar, ocea ad atmosphere activities [2]. May of researchers cosider gradual icrease i global temperature ad oceas due to icrease i greehouse gases as the most importat factor i climate chage. Global warmig of the Earth caused two importat pheomea i recet cetury: icrease i average global temperature ad icrease i sea level cosequetly, while eve small chages i hydrological variables ca lead to cosiderable chages i water resources, climate chage has a cosiderable ifluece o precipitatio, evaporatio, surface ruoff i regioal ad local scales [3]. The egative effects of chage of climatic variables o the Earth climate ad various systems has made this pheomeo which has bee cosidered as the most dagerous problem amog te huma-threateig issues i the 21st cetury [4]. It is worth to say that i this classificatio the threat of massacre weapos stads i third place. Climate could become warmer or colder ad average value of each factor of it ca be icreased or decreased over time. By chagig climatic variables, other

2 America Joural of Evirometal Protectio 29 systems which are affected by these variables such as water resources, agriculture, eviromet, health ad ecoomy will chage [4]. With the developmet of models ad umerical tools, statistical modelig were developed by usig advaced statistical methods ad based o the log-term elemets, pheomea ad major climate causes. The ivestigatios which are coducted by Katsoulis i 1987 [5], Karl i 1988 [6], Galbraith ad Gree i 1992 [7], Graf et al., 1995 [8]; Bruetti et al 2000 [9], Yuu ad Hoshio i 2003 [10], Li et al. i 2004 [11] ad Eyi 2014 [12] are some of related researches i this area. IPCC provided the primary series of emissio scearios i 1992 which is called IPCC (IS92a-IS92f). I these scearios, the amouts of greehouse gases will icrease with a fixed rate util I 1996, i order to update ad replace IS92 scearios, a series of emissio scearios called as Special Report of Emissio Sceario (SRES) was published to study the climate chages. Emissio scearios were developed to explore the future developmets i the global eviromet ad provide a special referece for emissio of the greehouse gases ad particulates i the atmosphere. SRES defies four mai emissio scearios as A1, A2, B1 ad B2 to describe the relatio betwee the emissio of greehouse gases ad suspeded particles i the atmosphere ad their effects o differet parts of the world durig the 21st cetury. These scearios have bee developed based o emissio factors of greehouse gases such as populatio, ecoomy, idustry, eergy, agriculture ad lad use [13]. IPCC has preseted four major assessmet criteria i field of climate chage (FAR -1990, SAR -1995, TAR ad AR4-2007). Use of preseted GCM models i AR i climate chage study has icreased cosiderably sice 2007 i compariso with preseted models i previous reports. The output of these models from Data Distributio Ceter (DDC) is available which was established based o the proposal of task group o data ad sceario support for impact ad climate aalysis (TGICA) i 1998 [1]. 2. Methods ad Materials 2.1. Geeral Circulatio Models Geeral Circulatio Models are developed to simulate curret climate o the Earth ad are able to predict future climate chage o the Earth [14]. These models were itroduced ad used based o Philips s persoal ivestigatio for the first time i the 1960s. Atmosphere Geeral Circulatio Models solve cotiuity equatios for fluid dyamics i spatial ad temporal discrete scales, ad their structure is the same as umerical weather predictio models. The mai differece is that i these models the weather predictios have bee doe i a shorter period of time (a few days) by defiig the iitial coditios precisely ad their accuracy is limited to a regioal with dimesios less tha 150 kilometers. But the etwork which is defied for GCM may iclude some geographic latitude ad logitude to simulate log-term weather [3]. I early GCM models, physical characteristics of the atmosphere at the Earth's surface were used as boudary coditios, but recetly i these models atmosphere-ocea boudary coditios are used for ocea modelig ad surface temperature ad soil moisture are used for Earth s surface. Oe of the major weakesses of these models is the disability to modelig the effects of clouds o the atmosphere ad iadequate accuracy to express the effects of hydrological variables such as lad use. I geeral, GCM models have better performace to simulate ad predict large-scale climate evets such as assessmet of eormous storms rather tha expressio of local ad regioal climate processes such as raifall-ruoff process [3]. Geeral specificatios of AOGCMs, IPCC fourth Assessmet Report ad relevat scearios that were used i this study are show i Table Dowscalig Due to computatioal limitatios, aalysis of geeral climate predictios have bee doig by limited ceters which are equipped with specific supercomputers for these calculatios. Curretly, more tha 40 orgaizatios i the world have developed differet models of geeral circulatio for the plaet Earth. Oe of the major limitatios i usig the output of GCM models is havig large-scale computatioal cells i terms of their spatial ad temporal which does ot have required match to hydrological models. Differet methods exist to produce regioal climate scearios from climate scearios of GCM models, which are called small scalig of these methods. I proportioal method usually mothly ratios are achieved for historical series. For this purpose, it is ecessary to produce scearios of climate chage for temperature ad precipitatio at first step. I order to calculate the climate chage sceario i each model, the differece values for temperature (equatio (1)) ad the ratio of raifall (equatio(2)) are beig calculated for log-term average i each moth i future periods ad basic simulated periods by the model for each cell of the computatioal grid [15]. T = T T (1) i GCM, fut, i GCM, base, i Pi PCGM, fut, i P CGM, obs, i = (2) I the above equatios ΔT i ad ΔP i idicates climate chage scearios of temperature ad precipitatio for log-term average for i moths (12 i 1), respectively. T GCM,fut,i is simulatio of log-term average of temperature by the GCM for i moths i future periods, T GCM,base,i is simulatio of log-term average of temperatures by GCM i the same period with observed period for i moths. P CGM,fut,i is simulatio of log-term average of temperature by the GCM for i moth i future periods, P CGM,obs,i is simulatio of log-term average of temperatures by GCM i the same period with observed period for i moths [16]. Because of the large computatioal cells i GCM models, simulatio of climatic fluctuatios is associated with turbulece. I order to elimiate these turbuleces, usually istead of direct use of GCM data i climate

3 30 America Joural of Evirometal Protectio chage calculatios, the log-term periodic average of data is used, the Chage Factor method is used for miimizig scale of data. I Chage Factor method to make careful time series of climatic sceario i future, climate chage scearios are added or multiplied i observed values. T = Tobs + T (3) P = Pobs P (4) I the above equatios, T obs ad P obs are time series of observatio temperature ad precipitatio i the base period, respectively. T ad P are time series of climatic scearios of temperature ad precipitatio i future period, ΔT ad ΔP are climate chage scearios of miimized scale of temperature ad precipitatio. Table 1. Specificatios of Used AOGCMS i This Study i DDC Related to the IPCC Fourth Assessmet Report Model Name Fouder Group Simulatio Sceario Atmospheric Separatio Power Referece CSIRO Mk3 ABM (Australia) A2, B1 1/875 * 1/875 Gordo et al. (2002) [18] CGCM3 CCCMA (Caada) A2, B1 3/75 * 3/75 Kim et al. (2002, 2003) [19], [20] HadCM3 UKMO (UK) A1FI, A2, B1 2/5 *3/75 Pope et al. (2000) [21] 2.3. The Study Regio Based o the water master pla of Ira, large SefidRood River basi is divided to 17 sub-basis ad upper basi of Talegha with 960 Km 2 area is located i east of SefidRood basi ad covered 2.5% of its surface. The upstream of Talegha catchmet is located i cetral Alborz Moutais ad the most importat feature is its high altitude ad steep slope. The average elevatio of basi is 2665 meters above sea level ad its maximum ad miimum height is 4300 ad 1390 meters, respectively. Also 50percet of Talegha catchmet has more tha 40% slope ad its geeral directio is east-west. Distributio of precipitatio i its differet locatios varies betwee 250 ad 1000 mm per year, also aual average raifall i the etire of basi is 600 mm. Legth of Talegha River is 85 meters, which is located i this catchmet ad it has its ow maximum discharge i sprig [17]. Cosiderig to the time costraits of available data for raifall, temperature ad ruoff i a commo period i selected statios ad the eed for log period for usig raifall-ruoff model, period was chose. Raifall, temperature ad mothly ruoff data of selected basi statios were corrected ad completed. To obtai the average raifall of the basi, weighted average of the selected statios were used. Therefore, for each statio weighted average was take ito based o its elevatio ad area ad average level ad total area of the basi. Figure 1. The Upstream Basi of Talegha Figure 2. The Climatological ad Hydrometric Statios i Upstream Basi of Talegha

4 America Joural of Evirometal Protectio 31 Chart 1. The Log-Term Average of Mothly Raifall i Each Statio [17] Chart 2. Log-Term Mothly Average of Temperature i Talegha Basi [17] Accordig to the chart (1) the average of aual raifall is 600 mm i the basi ad the moths with the most amout of precipitatio are April ad May. For all statios, witer moths experiece more tha 45 millimeters of raifall. Joosta, Gateh deh ad Galidar precipitatio statios have high impact o average raifall ad cosequetly o catchmet ruoff accordig to its rate of precipitatio ad catchmet height. However, accordig to iformatio of Zidasht statio, the average temperature i this area is the 7.8 C. The absolute maximum temperature is 37 C i July ad miimum temperature is -18 C which is measured i March. As chart (2) shows, for temperature variable mothly data of Zidasht with elevatio of 2000 meters due to its lowest differece elevatio with the average elevatio of the basi (372'2 m), this statio was cosidered as the basis ad accordig to elevatio differece betwee Ziadasht statio ad the average elevatio of the upstream basi of Talegha, with use of a temperature gradiet ad height, temperature data related average basi would be calculated. Because of limitatios i available raifall ad temperature data i the study area, period which was commo amog all statios was chose as the base period. I order to evaluate the performace of selected GCM models i simulatio of regioal climate variables, while A2 emissio sceario shows stricter coditios for the status of greehouse gas emissios i future periods tha other scearios emissios, it was cosidered. The mothly precipitatio ad temperature data selected from GCM models that cotai the timeseries variables of computatioal cells surroudig the Earth's climate, were take from CCCSN, ad mothly precipitatio ad temperature data for the base period related to computatioal cell which was located i selected statios of the basi (origial cells) were extracted, after that, 40-years average of mothly precipitatio ad temperature of the cells were determied. Fially, these amouts were compared with 40 years average of mothly observed precipitatio ad temperature of basi i base period Validatio Criteria ad Methods I statistics, correlatio refers to ay statistically sigificat relatioship betwee two variables, Pearso correlatio coefficiet has bee developed by Karl Pearso based o a origial idea of Fracis Galto, which measures liear relatioship betwee two radom variables. The correlatio coefficiet ca have values betwee -1 to +1 i which if the correlatio be close to +1, correlatio is more ad direct, ad if correlatio be close

5 32 America Joural of Evirometal Protectio to -1, correlatio is more but idirect ad zero mea a lack of correlatio. I this study, the Pearso correlatio coefficiet was used to compare the results of geerated data with observed oe based o defiitio for a statistical sample with couples (O i, P i ) we have: r = (O i 1 i O)(Pi P) = 2 2 (O i 1 i O) (P i 1 i P) = = (5) The mea absolute error (MAE) is criteria to measure how much predicted results are close to desirable oes. This criterio is measurable by the followig equatio: 1 MAE = Oi P i i = 1 (6) Root mea square deviatio (RMSD) or root mea square error (RMSE) is a commo measurig criterio that is calculated from the differece betwee the predicted values by model or estimator ad the observed data. I fact, RMSD idicates the sample stadard deviatio from the predicted values ad the observed data. These differeces are called residual whe calculatios are estimated from samples ad are called forecast error whe are predicted out of sample. RMSE is a acceptable measure to compare the predictio errors of a special variable that is measurable by the followig equatio: 2 i 1 (O i = P i RMSE = ) (7) I all equatios O i is the observed data, P i is estimated value, O is the average of observatioal data, P is the average of estimated data ad is the umber of data. Figure 3. The log term average of precipitatio: Observed vs CGCM3, CSIRO Mk3 ad HadCM3 models Figure 4. The log term average of temperature: Observed vs CGCM3, CSIRO Mk3 ad HadCM3 models

6 America Joural of Evirometal Protectio 33 Table 2. Validatio Criteria of AOGCMs Model Raifall Temperature R 2 RMSE MAE R 2 RMSE MAE CGCM CSIRO Mk HadCM Results Matrices Figure 3 ad shows the 40 years average of precipitatio of basi i compariso with the average of the same period which is calculated by CGCM3, CSIRO Mk3 ad HadCM3 models. Figure 4 ad shows the 40 years average of temperature of basi i compariso with the average of the same period which is calculated by CGCM3, CSIRO Mk3 ad HadCM3 models. Table 2 shows the validatio criteria of AOGCM models i estimatio the precipitatio ad temperature i compariso with observed data. 4. Coclusio Compariso of log-term average of the results of CSIRO Mk3 ad CGM 3 models with the observatioal dada idicates that although both models were able to estimate the geeral tred of raifall i the basi, there was a dramatic differece betwee calculated ad the log-term average of basi. Therefore, with the except of what is calculated i October, July ad September which the values are partly close to the observed data, i most cases, these two models have predicted the amout of precipitatio about the half of actual amout of it. I additio, although CGM3 ad CSIRO Mk3 model have calculated similar amouts i October ad Jue, i other cases they have ot show a acceptable performace. It seems that although all studied models did ot gai much success to forecast precipitatio i August, HadCM3 shows better performace i compariso with two other models which have predicted cosiderably less amouts of precipitatio for all periods, with the exceptio of raifall predictio for April ad May which is sigificatly more ad for August which is close to zero. I compariso of models performace i estimatig the temperature, it seems that all of the models have bee able to estimate the overall tred of temperature i a relatively acceptable patter. CSIRO Mk3 estimated precise temperature i October, but the forecasted temperature i November, December ad March are much higher tha the average of basi ad from April to September lower temperatures are estimated i compariso with other models. CGM3 estimated sigificatly high temperature from April to August i compariso with the average temperature of the basi. O the other had, although HadCM3 estimated low temperatures for all of the time period, it aticipates favorable tred for the chages ad shows relatively fewer differece i compariso with CSIRO Mk3 ad CGM3. I terms of the validatio criteria, all metioed models show high R 2 ad relatively low RMSE ad MAE estimatig the temperature which meas high depedecy of calculated results with observed data with low errors. However, compariso of the performace of HadCM3, CGM3 ad CSIRO Mk3 models i simulatio of precipitatio ad temperature shows that HadCM3model has better performace. I coclusio, it ca be said that i compariso of CGCM3, CSIRO Mk3 ad HadCM3 models i estimatio of the effects of climate chage o temperature ad precipitatio i the Talegha basi, although HadCM3 predicts precipitatio more tha the average of basi ad this model predicts highest ad lowest raifall ad temperature i most moths respectively, it ca be cosidered as a acceptable model that for estimatig temperature ad precipitatio with optimal performace for climate chage studies i this basi. Refereces [1] IPCC 2007a, Climate Chage: The Physical Sciece Basis. Cotributio of Workig Group I to the Fourth Assessmet Report of the Itergovermetal Pael o Climate Chage. Cambridge Uiversity Press, Cambridge. [2] J. Buchdahl, A review of cotemporary ad prehistoric global climate chage. Chester Street, Machester M1 5GD: Machester Metropolita Uiversity, [3] S. Karamooz, M., Araghy ejad, Advaced Hydrology. Tehra: Amirkabir Techology Uiversity Press, [4] L. O. Mears, F. Giorgi, P. Whetto, D. Pabo, M. Hulme, ad M. 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