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1 ! "#$ %! &# '(( ) "#) *+!,$ -.!"#$ %! &# '((,/ 01! "#$ %! 2(3 45 "# %!!,"( 6!# leila.forouhar@ut.ac.ir: (>?3= &# '(( <(6 89 : (3 3 ;1. %7?: C?D "?(? < *#5 6 "*45 EF 0(?: 0?(.# *J 6 I# H81 'G =# "%,89 %( 6L.I 0(.) 6L* "8M,=# "% 1 K< 6@*N(.' ) 6 "*45 EF "GJ 'G 1 H?/N B(?.'??) M P 1 0( * 6L.I 6J <( 6@*N &9 O*9?:???? *?1??? *?8I %845 (*F.)" 6"*45 EF K<,,,89 ::Q 8 #$..%./ -%) (, #$ $$% &'())* +,! " 6-1 +( ,+8.$(& () +$74,/ 5* 6%$% +,% #12 3 () 2 7..% ()(: + &BE +,CD 5*@ AB ' GCMs <= >)2 +,;%*:..% 6%F 6) ) &G HI +,;% 4 6)%D (), #$ AB,/ + 1 Data Mining Downscaling Model 2 General Circulation Models

2 2 1 +,>(. +( +,>( $) +,>( :%F +%&B@J 6%<= & ) ) & AB,/ +,>( &.Q().[1]%.,). L.M N. ) ( <= >)2 +,;% +,+' &@F $) AB,/ 6.2 &. &.).:%.,).(.A.BS(8. +., A.B,./ +.@ ( +( R ( +( >X. C.) &..[2]. 2( +.,>(., 1).U %.. +%& ) +,>( :%F +%B -.[<,.HI ( 8..%.F. 6) ) Z*. +( +,>( Y<= $) >( & AB,/ D ,&@.F [5].:() ;%. C.a +./6) +,_ [4] E: ] - 2( [3] E: - 2( &. GCM +.,*: AB,/ + [7] -@d() +,#F +( +2)$ >( [6] e.i #.BBD R. &./ +( AB,/ + )* +,( 81 L &<*' A.B,./ &. 6. %..E:. 2( R ( >' f$j ' +(;% #$... SDSM 12.% 6%F &12 (/ &12 ( 6)H )(.[3])') +* +, 6%.F 6) ) AB,/ ( & ( 8 &@G*' 6)H GCM& '( *: 9Q &GE() Model tree MARS+./6) ) +.,>( ' 6)H - SDSM&d - / (: &/ ;% () 6) )&G. (2012) -(<, C/ R - gd,h ' $<Q i%j>(h &( 8 &@G*#$. 6%F, 1 A.B,/ 6)<I (#$5-())* m 9$( +,( 8 -' ().[2] 6%F A.B,./ ' C.jQ n$. ;.<G!(.j&.. (..! " $'( ().%,) LM - +@ ( &.J&.9Q o. #.<I +. 6%F 6@/ _$p(%, +,;% +)( - = & >( -[<, +* +, 6)' #.<I B. D q%, - = &&9Q ( g$) +)$( ().%2 ( 6)H )(.. &.1$7!(.j.I ).$(' 6)H..!BBDa/ 1!) ();<G%$1& &* &/)F!.jU:.9 ( +(/-[<, &9Q +,2h$#1g 3 ()' F +,+' 6) C) & ()&.9Q +.,.2h$ B.] -)/ sd L) )$( 2).[8] B )$( 6) #BBD: )B )(r: &.12!(j!BBD&&) ().[9])F D - +$ 8 ' ( GCMABS(8 +, t@(. 6%F6(F uu:#$ () 13 & +)( U1 ( AB,/ & C/!N)G' 6)H (2001) (<, Landman %Q&_$)8 R ' </& )& &&GE#$ () ( AB,/.%: ) * +B$1 () % 12 1 Dynamical downscaling 2 Statistical downscaling 3 Synoptic weather typing 4 Stochastic weather generation 5 Regression 6 Linear regression 7 Polynomial regression 8 Data mining 9 Model tree 10 Artificial neural networks 11 Support Vector Machine 12 Statistical DownScaling Model 13 Perfect prognosis equations

3 &. NCEP 1.=XJ _. +.,6) ) 6)H )(!N)G v I + 1$7!(j R ' R.[9] 6%F &12(/ + &.Q E: - &@F +,;%)<= &$B& + &GE()(2002) Whitfield &@F +,;% + +$2 &GE#$ n$.%: ) )/()&9Q21()-$*BAB,/ + R ( + () +, +,&@F $ C) & #$.[10] 6%F $'( + &Q E: - 2( # E:] 6%[ 2 &.9Q. (.. + RVM +@ +( AB,/ >( _$(2008) Mujumdar 2 &xp #xp +,6 ()%, Mahandi&:)( +. 4 ' AB I (3& * + &GE()(2010) 6)H. (<, Tisseuil $5 () ANN ABT 5 GAM 4 GLM 3 +.,>( '.! " $'( 5* &:)(-$* AB,/.[12]%)/ 6)H A.B,./ () >( #.$.$'( +. +)(.&.GE )<= 6D 1G' y fbd #$ (). 6%F 6)( 5 H n$ : () &12!(j ( & <= >)2 +,;% +,*: E *-2 6L.I * 6 I# #. $1 * G 3 ' / Q &:/ 8$ &9Q +,- ' $,< &9Q #$. 6%F <F = F ;J & () &9Q #$ 6%<= < &12 () ( - ': - LX$ - )/ - %<, 6d/ S(8 &9Q$' H, & &9Q #$ &:/ 8$ &9Q G m & &*. - 6d/ - ':!=XJ fbd #$ (). B C 2 5 C -]( #' } :) C C + -I %@= &:/ &9Q ( B G (1)CF (). 6%F 6)H AB,/ + -]( +(%, 6g$. 6%F &x( (d/()-](&9q$' * "*45 EF )( +,$(. 6%F 6)H 6 HadCM3 ;% +,*: ' 3 )(&BE() ( AB,/ + +.* n$. %./. (./&'( +,6) ) ;% &$ &&*.%, B2 A2 +,$( 6)H )( 1 National Center for Environmental Prediction 2 Relevance Vector Machine 3 Generalized Linear Models 4 Generalized Additive Models 5 Aggregated Boosted Trees 6 Hadley Centre for Coupled Model, version 3

4 +...<( '...,6) )#...$... &...12(... 6)H... )(... f...bd #...$ () HadCM3;%... &...'(.% 6%F v I (d/ ] *] +,- ()-](&9Q$' &:/ &9Q +2( G :(1)H%) * *!3 65*4+ M *1,/ +,>( L< +@ + &BE AB 6%F ABS(8 +,gd # M R ( )M$.%.F..I NCEP.=XJ _. 6%.F C.D' +,6) )-',gd fbd #$ (). +( AB

5 .. &*() 2/5() 2/5NCEP+,6) ) +%&@F &Q() &*() 2/5 3/75HadCM3;% +%&@F &. L'N.. 6%.F 6)H. HadCM3;%!=XJ +%&@F +( 6%F +%&@F' NCEP+,6) )' #$ +.,: #.[<,.. 6%.F C.jQ!.=XJ $-() A / 6' () n$ CD &/ / & t +,gd 6%F sd &Q#$ () 6%F ; &@ g@<, ):,gd6'( & ) _$ )(. +.,g.d )%.G 4. #.$ &. &12( ()(&:/&9Qq J D &@F' 629 t.b )%.G) 26(NCEP 6%.F C.D' +,*:' gd +, )%G)) 936 m<m () 6)H -.' 4 +,gd &=<M I +.(4(6%F sd +,: )%G) 9((/7&@F' 6%F &12 3(). 6%F 6)H MATLAB( 81 L ())* + &Q- 2( >( ' (/7 +gd936 J % C) #<,&. +/6) ) +,>( ' 6)H SDSM&1$&G %F - d &/&g<, &.'( +.,.*: A.B,/ + +( ;%_$ SDSM.$' ) SDSM(: (&&jx:(j& e.i 1).U )%.= 6. %..E: 2( R ( >' f$j ' ;%#$. GCMs 1 () SDSM(:..%/ ei $, +,+ )M$ & L % 2( ;% *: $)B 5 &$B (>(. YXa) 6%F I ' y SDSM() %$ CF #$ ' &/(E<,. 6%F 6) )-d(2)cf,/ %G &Q().)F 6@/ ;% yw 6%F #G;%(: NCEP+, -' 4 +,gd 2 #$%..)')..., %&;% NCEP+,gd ' 6)H!(j().)F LM!(j ) & AB!(.j().).F% )*- + %,d +,6) )&/ + 6() () 6%F ' $,+ &/ G 3 +.,6() +. 6%.F. ' $,+ %& g$) -& $ $( %&;% GCM+,gd ' 6)H.[3])') 6%$ SDSM_<F (: :(2)H%) 5 4 _.</,g.d &.=<M.I &. 6%F,gd # x8* g@<, g@<, SDSM() 1 Ensembles 2 Weather Generation 3 Scenario Generation 4 Correlation 5 Partial Correlation

6 1,.1 %., m. L%.= m Q ) &_H C &/ $, + ( JF AB,/ - 2 &. ) &<*' < +, $ + 8 JF ] AB,/.[2] (&'( 1!= >( 3) %/ %/ -..M R. ( I.d..,g.d.I &.Q() SDSM+.,!.H ' $.)((/ +(. A.B,./ +.,>(.<. &ƒ >( Ca G9 6%F 6%F +%&@F +,gd R.D() ;%#$ &$ &&*.%/< 6)H,gd I + + 6%F #G ' >( ' () -. #.$ '.)()).*( 8.1 L. #$ ())*-22 +,>( ' 6)H - 6%F &F. MATLAB. 6%F 6)H + &Q - 2( ' 9Q fbd 6@./ &. '(. ( #.<I +..$' +,;% fbd #$ () 6)H )( AB,/ ;% () :%F 3 (SDSM() 6)H )( MLR) 6% E: - 2( (MARS MT +.,>( -. '.$5 () ).F. &123 () +' ;% () 8 g@<, ): SDSM%<, C.Q &./ &./../ & L'N.%,)LM - +@ ( AB,/ %/ I ( 5 #$5 )*. SDSM&d AB,/ +%G #&4G B( 6V-3 +.,6() +. ;. e.i +.,6.() 6%.F +'. ;%. 6%F 6%,dR $)B #g(3)cf() %j() 25 + %,d!=xj %j() 75fBD #$ (). 6%F 6)( M Dj +'. &@.F +. ).<= %.$. CF #$ ' &/(E<,. 6%F 6)H M Dj +!=XJ +.,.*: +)(!.=XJ (.G q.d (4)C.F()...E!.=XJ &.,R. $)B#g #.$ &.&.*... 6%F &x( M Dj + ; ei +,6+ 6%F +' &@F %,.d+.,6)) (.G q.d &_$)8(G q D +) %= %() +( )$( $ CF.. 6%.F. ( %,.d. ( () R 6%F &@ D ( (5)CF().)F $'( %.F 6)( ,;. + D ( ' + (6)CF ()#[<, +.., %. ABS(8 +,gd B AB,/ () / )<=,( )<#$ &&* m.9 % +%Q $ H/ )@5 + $,(, (&x( )F $'( 4 3 )( +,;.%F!GE 1 Conditional Downscaling 2 Unconditional Downscaling 3 Multiple Linear Regression

7 "+#'1/( ماه (ژانويه تا دسامبر) (ميليمتر بر کيلومترمربع) رواناب *X.(W. محاسباتی (ميليمتر بر کيلومترمربع) رواناب محاسباتی ماه (ژانويه تا دسامبر) M Dj +,6() + ( &, D %,d $)B#g&$B :(3)H%) "+#'1/( محاسباتی ماه (ژانويه تا دسامبر) (ميليمتر بر کيلومترمربع) رواناب رواناب (ميليمتر بر کيلومترمربع) *X.(W. محاسباتی ماه (ژانويه تا دسامبر) M Dj +,6() + ( &,(G q D %,d $)B &$B:(4)H%) "+#'1/( رواناب (ميليمتر برکيلومترمربع) رواناب محاسباتی (ميليمتر بر کيلومترمربع) رواناب محاسباتی (ميليمتر بر کيلومترمربع) *X.(W. رواناب (ميليمتر برکيلومترمربع) M Dj +,6() + ( &, R $)B quantile-quantile( )< :(5)H%)

8 محاسباتی رواناب (ميليمتر بر کيلومترمربع) ( &, D %,d $)B' + :(6)H%) 6)( ,; + %,d ( &, R $)B ' + (8) (7)+,CF () #.$... 6%.F. ( ,; + 6%F &, R $)B -;@)& 6%F () $5 (). 6%F LM B2 A2 +,$( + HadCM3 <= >)2 ;% +,*: ' 6)H $)B ()( ,;. ) %,.d 6() +. ; ei +,6 + &, R $)B #g(9)cf! " #123() CF #$ &&*. 6%F &x( ( ,; ) 6%$6() &d $)B &$B. C$( +,6 ()-](&9Q$' ( )F (/7 +$( )!91 D 6%$% 6%,.d. ( (%.B() +.d,./ A2+$(. B2 +$( n$ ().%/ %,/ 2.)F +.,_. ' 6)H.. &./ +(. A.B,./ ;%.%.F +,I ()&/(E<, 9Q &GE().[2] 6%F &:F! " $'( + %< +( 8 - = & 6%F 6) )&G +/6) ) A.B,./ ()&./ m.9 #.$ &&*. 6%F &:) ( B AB,/ &( 8 #$ ' 6)H ;%. $(./ ).F.< &.12 3 () r:!ju: 9 ( +(/ -[<,&9Q +,2h$ ( B #.$ n$... '( YX/fBD #$ n$ () AB,/ %$1 () C = #$ B] -)/ sd (). 2 C$( +,6 () (,/ +$2 &GE

9 رواناب A2 (ميليمتر بر کيلومترمربع) A2+$( R 6%F ( %,d ( &, R $)B ' + :(7)H%) رواناب B2 (ميليمتر بر کيلومترمربع) B2+$( R 6%F ( %,d ( &, R $)B ' + :(8)H%) ( (ميليمتر بر کيلومترمربع) رواناب (W. (ميليمتر بر کيلومترمربع) رواناب سناريوی B2 دسامبر) تا (ژانويه ماه سناريوی A2 دسامبر) تا (ژانويه ماه 1961+,; ) %,d6() + ( &, D %,d $)B#g&$B :(9)H%) ( ,; ) 6%$(2000

10 &G-4 [1] Mearns, L.O., Giorgi, F., Shields, C., McDaniel, L. (2003). "Climate scenarios for the southeastern US based on GCM and regional modeling simulations" Climatic Change 60, [2] Tavakol-Davani, H., Nasseri, M., Zahraie, B. (2012). "Improved statistical downscaling of daily precipitation using SDSM platform and data-mining methods" Int. J. Climatology, doi: /joc.3611 [3] Wilby, R.L., Dawson, C.W., Barrow, E.M. (2002). "SDSM a decision support tool for the assessment of regional climate change impacts" Environmental Modelling & Software, 17, [4] Hewiston, B. (1994). "Regional climates in the GISS general circulation model: surface air temperature" J. Climate, 7(2), [5] Li, X., Sailor, D. (2000). "Application of tree-structured regression for regional precipitation prediction using general circulation model output" Climate Research, 16, [6] Fistikoglu, O., Okkan, U. (2011). "Statistical downscaling of monthly precipitation using NCEP/NCAR reanalysis data for Tahtali river basin in Turkey" J Hydrologic Engineering, 16(2), doi: /(asce)he [7] Sachindra, D.A., Huang, F., Barton, A.F., Perera, B.J.C. (2013). "Multi-model ensemble approach for statistically downscaling general circulation model outputs to precipitation" Quarterly J. the Royal Meteorological Society, doi: /qj.2205 [8] Xu, C.Y. (1999). "From GCM to river flow: a review of downscaling methods and hydrologic modeling approaches" Progress in Physical Geography, 23(2), [9] Landman, W.A., Mason, S.J., Tyson, P.D., Tennant, W.J. (2001). "Statistical downscaling of GCM simulations to steramflow" J. Hydrology, 252(1-4), [10] Cannon, A.J., Whitfield, P.H. (2002). "Downscaling recent streamflow conditions in British Columbia, Canada using ensemble neural network models" J. Hydrology, 259(1-4), [11] Ghosh, S., Mujumdar, P.P. (2008). "Statistical downscaling of GCM simulations to streamflow using relevance vector machine" Advances in Water Resources, 31(1), [12] Tisseuil, C., Vrac, M., Lek, S., Wade, A.J. (2010). "Statistical downscaling of river flows" J. Hydrology, 385(1-4),