Prediction of frost occurrence by estimating daily minimum temperature in semi-arid areas in Iran

Transcription

1 Ira Agricultural Research (208) 37() 9-32 Predictio of frost occurrece by estimatig daily miimum temperature i semi-arid areas i Ira Shiraz Uiversity M. H. Joreoosh *, A. R. Sepaskhah Departmet of Irrigatio, College of Agriculture, Shiraz Uiversity, Shiraz, I. R. Ira * Correspodig Author: joreoosh@yahoo.com DOI: /IAR ARTICLE INFO Article history: Received October 206 Accepted 9 Jauary 207 Available olie 8 Jauary 208 Keywords: Frost Dew-poit Relative humidity Miimum temperature ABSTRACT- May fruits, vegetables ad orametal crops of tropical origi experiece physiological damage whe subjected to low temperatures. Protectio of plats from the effects of lethally low temperatures is importat i agriculture, especially i horticultural productio of high value fruits ad vegetables. The objective of this study was to develop a simple model to predict the daily miimum air temperature for predictio of frost occurrece i Bajgah ad Kooshkak semi-arid areas, Fars provice. Iitially, the relatioship betwee the miimum temperature of the early morig of a day with some meteorological parameters of the previous day was developed. Meteorological parameters used i this aalysis are daily relative humidity, wid speed, pa evaporatio, raifall, sushie hours, ad estimated dew-poit temperature. Dewpoit is a importat parameter which is related to the miimum temperature i differet moths with low temperature i Bajgah ad Kooshkak areas. May daily weather parameters used i the regressio aalysis showed o sigificat relatioship with the daily early morig miimum temperature, except the dew-poit ad relative humidity. The regressio equatio betwee the differeces betwee dew-poit ad miimum temperature with relative humidity as a simple model was proposed to be used to predict the miimum temperature ad subsequetly frost occurrece i the study regios. This model was validated by idepedet data set with a acceptable accuracy for the study regios. INTRODUCTION Food productio is oe of the mai problems i the world. Agricultural capability for food productio i each regio depeds o weather ad climate coditios. The protectio of plats from the effects of lethally low temperatures is importat i agriculture, especially for horticultural productio of high value fruits ad vegetables. Weather is usually described i terms of a series of measuremets ad observatios that iclude temperature, wid, sushie, cloud cover ad precipitatio. Plat physiology, seed germiatio, polliatio, growth, photosythesis ad material trasport withi the plat are sesitive to climate coditios i differet plat growth stages. Oe of the meteorological issues for may agricultural systems is frost occurrece. Differet plats show differet reactios to low temperatures, ad it depeds o the health of the plat, maturity, growth rate, ad growth stages. Time of frost occurrece shows differet resistace of plats to frost (Vatskevich, 985). Low temperature ijury (e.g., chillig ad freezig) ca occur i all plats; however, the mechaisms ad types of damage vary cosiderably. May fruits, vegetables ad orametal crops of tropical origi experiece physiological damage whe subjected to temperatures below about 2.5 C, hece well above freezig temperatures. However, damage above 0 C is chillig ijury rather tha freeze ijury. Freeze ijury occurs i all plats due to ice formatio i plat. Crop plats that develop i tropical climates, ofte experiece serious frost damage whe exposed to temperature slightly below zero whereas most crops that develop i colder climates ofte survive with little damage if the freeze evet is ot too severe. Frost damage may have a drastic effect o the etire plat or affect oly a specific part of the plat tissue that reduces yield, or merely product quality (Roseberg, et al., 983). The forecast of frost occurrece requires complicated decisio aalysis that uses coditioal probabilities ad ecoomics. Accurate frost forecastig ca potetially reduce frost damage because it provides growers with the opportuity to prepare for frost protectio. The daily miimum temperature depeds o meteorological parameters such as mea air temperature, radiatio, wid, humidity, soil properties ad cover. I may practical cases, the oly iformatio oe may have is the daily maximum/miimum air temperatures, precipitatio ad sometimes solar radiatio, vegetatio cover ad soil type. The ability to

2 predict the occurrece of frost from this type of iformatio would be quite useful i agriculture (Cary, 982). Predictig the time of temperature fall to a critical value is importat for startig active frost protectio methods. I additio, the duratio of temperature below the critical value is importat for assessig potetial frost damage. Startig at the proper temperature is importat because it avoids losses resultig from startig too late ad it saves eergy by reducig the operatio time of the various methods at ay give time durig the ight. The critical time for startig ay frost protectio activity is oe hour before the time that the critical damage temperature is expected. This predictio method is fairly accurate; however, it is ot perfect (Syder, 2000). For the developmet of miimum temperature occurrece atlas, daily miimum temperature values were used i Fars provice (Ziaee et al., 2006). I this study, the dates of differet miimum temperatures were fitted to statistical distributio fuctios usig SMADA software. Log Pearso type ш ad Pearso type ш was determied as the best distributio for estimatio of the frost occurrece dates. The miimum temperature occurrece atlas was also determied by the use of occurrece probability ad geographical coordiates i SURFER. Usig these maps is useful for frost predictio for decisio makig to select the platig ad harvestig of crops (Ziaee et al., 2006). There are several methods of predictig the occurrece of frost. May ivolve a empirical relatioship betwee the miimum temperature ad dew-poit temperature (T d ). I Victoria (Australia) frost is reckoed possible if dew-poit is less tha 6 C, ad probable if it is below 0 C. Miimum temperature is deduced as equal to [T max + T d ]/2 mius a correctio which depeds o the wid speed ad cloudiess, where T max is the highest temperature reached the previous day (Bagdoas et al., 978). For preparatio of frost atlas i Fars provice, Ira, the miimum daily air temperatures at 27 meteorological statios were used. The values of miimum temperature rages of 0 C to -.5 C, -.5 C to -3 C ad below -3 C were cosidered as mild, moderate ad severe frosts itesities, respectively. The differece betwee measured ad estimated dates of frost was estimated by modified iverse distace weighted (MIDW) method. The method of MIDW was selected for preparatio of frost atlas i Fars provice, Ira (Didari et al., 20). Dew-poit ad relative humidity may be appropriate to predict the frost occurrece. The values of daily relative humidity i rage of 45% to 55 % i the eveig ca be used accurately for estimatig miimum temperature i the early morig of the ext day i Jahrom, Ira, (Nazemosadat et al., 200). I this study, for the values of relative humidity outside of this rage, the miimum temperature i the ext day was lower or higher tha the dew-poit of previous day, respectively. Therefore, it is idicated that daily relative humidity ca help to estimate the ext day miimum temperature. The purpose of this study was to develop a simple model to predict the daily miimum temperatures of early morig based o daily meteorological parameters of the previous day i Bajgah ad Kooshkak areas, Fars provice, for frost occurrece. MATERIALS AND METHODS The meteorological data from 982 to 2002 i Bajgah ad from 992 to 2002 i Kooshkak i the moths of April, May, October, November, December, Jauary, February, ad March were used for estimatio of the daily early morig miimum temperature from the weather parameters of the previous day for the frost forecastig. The relatioship betwee the miimum temperature ad the most importat climate parameters i differet moths was determied by simple regressio aalysis. The list of these parameters is show i Table. Table. Meteorological parameters used i this study Variable Defiitio Uit T max Maximum daily temperature C T mi Miimum daily temperature C T mea Mea daily temperature C RH max Maximum daily relative humidity % RH mi Miimum daily relative humidity % RH mea Mea daily relative humidity % N Daily sushie hours hour R Daily raifall mm U2 Wid speed 2 m height m/s E p Daily pa evaporatio mm Estimatio of Dew-Poit I this study, the daily dew-poit (T d ) is a importat parameter that should be estimated ad icluded i the regressio aalysis. To estimate the daily dew-poit (T d ) the values of maximum/miimum temperature, maximum/miimum relative humidity ad vapor pressure were used. The T d temperature i C is determied by the followig equatio (Alle et al., 998): T d l( ea ) = () 6.78 l( e ) a where T d is the dew-poit temperature ( C), e a is the actual vapor pressure (kpa). To calculate e a, we eed to determie e 0 (T), the saturatio vapor pressure i temperature of T i C as follows (Alle et al., 998): T e ( T ) = exp (2) T The value of e a ca be determied by three methods that are give i Eqs. (3) to (5) (Alle et al., 998) as follows: 0 0 e ( Tmi ) RH max + e ( Tmax ) RH mi e a = (method ) (3) 200 Method [Eq. (3)] is used i situatios where the measured values of maximum ad miimum temperature ad relative humidity are kow. 20

3 e e a = 0 ( Tmi max ) RH 00 (method 2) (4) Method 2 [Eq. (4)] is used i situatios where the accuracy of miimum relative humidity measuremet is low or suspicious ad we ca use maximum relative humidity. 0 0 RH mea e ( Tmax ) + e ( Tmi ) ea = [ ] (method 3) (5) 00 2 Method 3 [Eq. (5)] is used i situatios where miimum ad maximum relative humidity are ot measured ad the average relative humidity is available. I Eqs. (3) to (5) e a is the actual vapor pressure (kpa), e 0 (T mi ) ad e 0 (T max ) are the saturatio vapor pressure i miimum ad maximum temperature (kpa), respectively; RH mi, RH max, ad RH mea are the miimum, maximum ad mea relative humidity (%), respectively; ad T mi ad T max are the miimum ad maximum temperature ( C), respectively. Methods to 3 based o Eqs. (3) to (5) were used to determie the e a ad cosequetly T d i correlatio aalysis. Based o available measured data, the appropriate method may be differet although i determiig e a, the best suggestio is Method [Eq. (3)] accordig to Whitema (957). However, i this study, all three methods were used to determie e a for estimatio of T d i order to fid the appropriate method. I the preset study, the differece betwee calculated daily dew-poit ad the miimum temperatures of the early morig of the ext day is used as a tool to develop the simple model ad is showed by d as follows: d=t d (i)-t mi (i+) (6) where T d (i) is the daily dew-poit temperature i day i ( C) ad T mi (i+) is the miimum temperature i day i+ ( C). The relatioship betwee d values ad daily RH was developed as a simple model for predictio of T mi. The calculated daily dew-poits by the three methods i Eqs. (3) to (5) are displayed by Td() ad Td(2) ad Td(3), respectively, ad correspodig d values are show by d ad d2 ad d3, respectively. SPSS, Stat graphics, Curve Expert, Excel ad SMADA are soft-wares that were used to determie the best relatioships betwee data, liear ad oliear regressios, comparig multiple data sets i pairs or i groups, data impacts o each other, aalysis of variace, elimiate outlier data, ad statistical distributios ad occurrece probability of miimum temperatures. Statistical Aalysis There has bee a cocomitat ad deepeig iterest i comparig ad evaluatig the models accuracy. To assess the validity of models, statistical aalysis is used. Some of the most importat statistical parameters of model evaluatio aalysis are the Normal Root Mea Square Error (NRMSE), Mea Absolute Error (MAE), Mea Error (ME), Idex of agreemet (d) ad Coefficiet of Nash-Sutcliff (C NS ). These statistical parameters are determied by Eqs. (7) to () as follows (Nash et al., 970., Willmott, 982): ( Oi Pi ) i= NRMSE = O MAE = P i O i i= ME = ( P i O i ) d C i= ( Pi Oi ) ( Pi O + Oi O ) i= 2 2 (7) i= = (0) 2 i= NS = ( Pi Oi ) ( Oi O ) i= 2 2 (8) (9) () where P i ad O i are the predicted ad observed values of a parameter, O is the average of observed data ad is the umber of observatios. Lower values of MAE, ad the values of NRMSE ad ME ear zero show a higher similarity betwee the measured ad estimated values i the model. The values of d ear to idicate the best agreemet betwee measured ad estimated values. Values of C NS rage from mius ifiity to, with higher values idicatig better agreemet. The values of measured ad predicted daily miimum temperatures by the simple regressio models were evaluated by usig Eqs. (7) to (). Furthermore, for evaluatio of the accuracy of the model, the relatioship betwee the measured ad predicted values were compared with : lie by Fisher F statistics. RESULTS AND DISCUSSION Probability of Miimum Temperature Occurrece Distributio fuctio as a result of probability aalyses by SMADA software was determied. Retur periods of miimum temperatures i the studied moths were evaluated i Bajgah ad Kooshkak. We determied the probabilities of below 0 C temperatures occurrece i differet moths with dager of frost occurrece. Results are show i Table 2. By kowig the miimum temperature for frost ijury of a plat, the ecessary steps to prevet the frost damage is aticipated. 2

4 Table 2. Miimum temperatures i differet retur periods i Bajgah ad Kooshkak areas Retur period, year Moth Bajgah Kooshkak April May Oct Nov Dec Ja Feb Mar For istace, the retur period for -7.5 C temperatures occurrece i May i Bajgah is 5 years. Furthermore, i April, every year temperature is expected to drop to -7.5 C i Kooshkak. Iformatio preseted i Table 2 is useful for providig some protectio actios to prevet plat ijuries by kowig the occurrece probability of miimum temperatures i these areas. Also, by kowig the values of miimum temperature, the crop type ad platig date ca be maaged properly. The autocorrelatio of miimum temperature of cosecutive days with differet lags i all years has bee aalyzed to kow the presece or lack of relatioship betwee them. If there is a relatioship betwee miimum temperatures of cosecutive days, further calculatios may be simpler; also we should be able to determie a relatioship betwee the miimum temperature of cosecutive days ad develop a simple usable model for predictio of daily miimum temperature. The results of the time series correlatio obtaied for the miimum temperature i Bajgah ad Kooshkak showed a sigificat correlatio of the miimum temperature i the cosecutive days with oe lag ad other lags were ot sigificat. The partial autocorrelatio coefficiets were 0.68 ad 0.77 for Bajgah ad Kooshkak, respectively with stadard error of ad for Bajgah ad Kooshkak, respectively. This idicated that there is sigificat relatioship oly betwee daily miimum early morig temperature with miimum early morig temperature of the ext day. This idicated that the miimum temperature of the cosecutive day with oe lag is related to each other ad lags higher tha oe showed o correlatio. Therefore, the relatioship betwee daily miimum temperature ad other weather parameters was ivestigated i the ext step. Relatioship Betwee Daily Miimum Temperature ad Other Weather Parameters Iitially, the relatioship betwee the daily miimum temperature ad some meteorological parameters was developed. The results showed i Table 3 idicated that the miimum temperature showed a sigificat relatio with dew-poit temperature estimated by three differet methods [Eqs. (3) to (5)] ad mea relative humidity. I other words, relative humidity ad dew-poit temperature were the most sigificat parameters correlated with the daily miimum temperature. It is evidet that daily relative humidity ad dew-poit sigificatly iflueced the daily miimum temperature of the early morig. The relatioship betwee the dewpoit of three methods ad the meteorological parameters are show i Table 4. I geeral, the coefficiets of determiatio (R 2 ) idicated that there is a better relatio betwee the dew-poit estimated by Eq. (3) [T d ()] ad other parameters. This supported the suggestio of Whitema, (957); therefore, the results of Method [Eq. (3)] were used i the ext aalysis. Table 3. Coefficiets of determiatio (R 2 ) betwee miimum temperature ad some meteorological parameters i Bajgah ad Kooshkak Weather parameter Bajgah Kooshkak T d () 0.55 ** 0.48 ** T d (2) 0.60 ** 0.63 ** T d (3) 0.59 ** 0.55 ** RH max 0.3 ** 0.2 ** RH mi 0.2 ** 0.6 ** RH mea 0.8 ** 0.24 ** U Rai Ep 0.00 * N **, *: Sigificat at % ad 5 % probability levels, respectively Relatioship Betwee Miimum Temperature ad Dew-Poit Differece with Other Weather Parameters The relatioship betwee d values (d= differece betwee daily dew-poit temperature (T d (i)), ad daily early morig miimum temperature of ext day (T mi (i+))) of method [Eq. (3)] ad meteorological parameters is show i Table 5. The relatioship betwee d ad average relative humidity showed higher R 2 tha other parameters. Therefore, d is used i the simple model for T mi predictio. The coefficiet of determiatio (R 2 ) for the relatioship betwee d ad average relative humidity i each moth ad for all combiatios for moths of the study period was aalyzed separately. Because of the possibility of outlier data etry i the relatioship, the results after removig the outliers were used i this study. 22

5 Table 4. Coefficiets of determiatio (R 2 ) betwee the dew-poit estimated by three differet methods ad some meteorological parameters i Bajgah ad Kooshkak Bajgah Kooshkak Weather parameter T d () T d (2) T d (3) T d () T d (2) T d (3) RH max 0.0 * 0.8 ** 0.0 * 0.32 ** 0.29 ** 0.34 ** RH mi 0.59 ** 0.27 ** 0.24 ** 0.67 ** 0.5 ** 0.40 ** RH mea 0.56 ** 0.29 ** 0.24 ** 0.69 ** 0.24 ** 0.45 ** U2 0.3 ** 0.7 ** 0.09 * 0.4 ** 0.09 * 0.09 * Rai 0.20 ** ** 0.22 ** 0.22 ** Ep 0.25 ** 0.24 ** 0. * N **, *: Sigificat at % ad 5 % probability levels, respectively Table 5. Coefficiets of determiatio (R 2 ) betwee the miimum temperature ad dew-poit differece (d) of method [Eq. (3)] ad some meteorological parameters i Bajgah ad Kooshkak Weather Parameter Bajgah Kooshkak RH max 0.24 ** 0.46 ** RH mi 0.59 ** 0.7 ** RH mea 0.60 ** 0.74 ** U Rai 0.27 ** 0.25 ** Ep 0.2 ** 0.04 N 0.8 ** 0.05 **: Sigificat at % probability level The equatio of liear relatioship ad coefficiet of determiatio (R 2 ) of the relatioship betwee d ad average relative humidity before ad after correctio i Bajgah ad Kooshkak are give i Table 6 ad Figs. ad 2, respectively. For the values of mea relative humidity betwee 65 ad 75 % i Bajgah, i all cases, the daily differece betwee dew-poit ad miimum temperature of the ext day is ear zero. I this rage of RH, we ca equate the daily miimum temperature to the dew-poit of previous day. This rule is applicable i the colder moths (moths with low average temperature) with high relative humidity (75 %) ad i the warmer moths (moths with high average temperature) with low relative humidity (65 %). For example, accordig to Fig. i March, with the mea relative humidity of 73%, the daily dew-poit is equal to the ext day miimum temperature. Whereas, i May whe the average temperature is higher tha March, the d=0 occurred with mea relative humidity of 65 %. Accordig to Fig., the value of mea relative humidity is above 75 %, that is usually characteristic of colder moths; therefore, the daily dew-poit is higher tha the miimum temperature of the ext day. I this situatio, it is suggested to subtract a few degrees from dew-poit for predictio of miimum temperature of the ext day. The corrected dew-poit value for each moth ca be determied by the equatios obtaied from Table 6. I the moths with low mea relative humidity (below 65%), which usually occurred i moths with higher temperatures, the daily dew-poit is less tha the ext day miimum temperature. I such cases, it is suggested to add a few degrees to the daily dew-poit ad use it i equatios i Table 6 to predict the T mi. The determiatio coefficiet (R 2 ) of the relatioship betwee the miimum temperature ad dew-poit i Kooshkak is higher tha that of Bajgah (Table 6). It might be due to the lower umber of recorded data obtaied for recet years with lower variability tha the recorded data i Bajgah. Accordig to Fig. 2, with higher values of mea relative humidity (over 66%) i Kooshkak, the daily dew-poit is higher tha the miimum temperature of the ext day. I case of low mea relative humidity (less tha 64%), the daily dew-poit is less tha the ext day miimum temperature. The corrected dew-poit value for each moth ca be determied by the equatios obtaied from Table 6. I case of mea relative humidity betwee 64 to 66 % i Kooshkak, the daily dew-poit is equal to the ext day miimum temperature i all cases. Therefore, i cases of relative humidity of 65 % i Kooshkak, the ext day miimum temperature is equal to the daily dew-poit. Daily mea relative humidity ad dew-poit were used i simple models of Table 6 to estimate daily miimum temperature of the ext day. Comparisos of the measured ad estimated T mi by the proposed simple models i Bajgah ad Kooshkak are show i Figs. 3 ad 4. The liear relatioship ad coefficiet of determiatio (R 2 ) of the relatioship betwee the measured ad estimated T mi i Bajgah ad Kooshkak are give i Table 7. Determiatio coefficiet (R 2 ) i Table 7 is sigificat at % level of probability, which showed a good relatioship betwee the measured ad estimated T mi by simple models i Table 6. The determiatio coefficiets (R 2 ) of all combiatios for moths i Kooshkak is higher tha those i Bajgah. It might be due to the lower umber of recorded data obtaied for recet years with lower variability tha the recorded data i Bajgah. I geeral, i both areas, the values of R 2 for all moth combiatios were equal or sometimes higher tha those for each moth; therefore, we ca use the equatio obtaied of all moth combiatios, eve better tha those obtaied for differet moths. I geeral, the relatioship betwee the early morig miimum temperature of the ext day ad daily dew-poit was sigificat i Bajgah ad Kooshkak. As the differece betwee the daily dewpoit ad the miimum temperature of the ext day is closer to zero, we ca equate tomorrow morig miimum temperature to the dew-poit of today with higher cofidece. These results are similar to those foud by Nazemosadat et al. (200). 22

6 (a)april (b) May (c)october (d)november (e) December (f) Jauary (g) February (h) March (i)all moths Fig.. Relatioship betwee d ad RH mea i the study period i Bajgah 23

7 (a)april (b) May (c) October (d)november (e) December (f)jauary (g) February (h) March (i) all moths Fig. 2. Relatioship betwee d ad RH mea i the study period i Kooshkak 24

8 (a)all moths (b) April (c)may (d)october (e)november (f)december (g) Jauary (h) February (i) March Fig. 3. Compariso of the measured ad estimated T mi by the simple models i Bajgah 25

9 (a)all moths (b) April (c)may (d)october (e)november (f)december (g) Jauary (h) February (i) March Fig. 4. Compariso of the measured ad estimated T mi by the simple models i Kooshkak. 26

10 Table 6. Coefficiets of determiatio (R 2 ) betwee d ad mea RH mea before ad after correctio i Bajgah ad Kooshkak Bajgah Kooshkak Period Liear equatio R 2 After R 2 Before R 2 After R 2 Before Liear equatio correctio correctio correctio correctio All moths d=0.28 RH mea ** 0.38 ** d=0.32 RH mea ** 0.56 ** April d=0.25 RH mea ** 0.35 ** d=0.34 RH mea ** 0.44 ** May d=0.30 RH mea ** 0.39 ** d=0.37 RH mea ** 0.60 ** Oct. d=0.30 RH mea ** 0.50 ** d=0.29 RH mea ** 0.59 ** Nov. d=0.24rh mea ** 0.49 ** d=0.32 RH mea ** 0.73 ** Dec. d=0.7 RH mea ** 0.20 ** d=0.32 RH mea ** 0.6 ** Ja. d=0.26 RH mea ** 0.36 ** d=0.27 RH mea ** 0.52 ** Feb. d=0.22 RH mea ** 0.30 ** d=0.32 RH mea ** 0.59 ** Mar. d=0.24 RH mea ** 0.29 ** d=0.36 RH mea ** 0.64 ** **: Sigificat at % probability level Table 7. Liear relatioships betwee the measured (T mm ) ad predicted (T mp ) miimum temperature for differet moths i Bajgah ad Kooshkak Bajgah Kooshkak Period Liear equatio R 2 Liear equatio R 2 All moths T mp =0.63 T mm ** T mp =0.92 T mm ** April T mp =0.69 T mm ** T mp =0.66 T mm ** May T mp =0.58 T mm ** T mp =0.5 T mm ** Oct. T mp =0.57 T mm ** T mp =0.68 T mm ** Nov. T mp =0.57 T mm ** T mp =0.79 T mm ** Dec. T mp =0.44 T mm ** T mp =0.60 T mm ** Ja. T mp =0.39 T mm ** T mp =0.69 T mm ** Feb. T mp =0.42 T mm ** T mp =0.66 T mm ** Mar. T mp =0.43 T mm ** T mp =0.64 T mm ** **: Sigificat at % probability level Model Validatio The measuremets of weather parameters from 2003 to March of 205 were used for validatio of the simple regressio models showed i Tables 8 ad 9. Comparisos of the measured ad estimated daily miimum early morig temperature (T mi ) for all combiatios for moths ad differet moths i Bajgah ad Kooshkak are show i Figs. 5 ad 6. The liear relatioships betwee the measured ad predicted daily T mi for each moth ad their combiatio i Bajgah ad Kooshkak are show i Tables 8 ad 9, respectively. For the liear relatioship where the slope is close to.0, it is close to : lie. This situatio occurred i the equatios for all combiatios for moths i Bajgah ad Kooshkak with higher R 2 ; therefore, we ca use this geeral equatio for all moth combiatios, eve better tha the equatios for differet moths. I this case, the higher umber of data made more similarity betwee the observed ad estimated values i the model. I geeral, the measured values of daily miimum temperature are fairly close to the predicted values due to o-sigificat slope ad itercept compared with.0 ad zero (Tables 8 ad 9). The low values of Mea Absolute Error (MAE) ad Mea Error (ME) of the relatioships betwee the measured ad predicted values i each moth ad their combiatio supported the accuracy of the estimatio. Lower values of MAE ad NRMSE showed higher similarity betwee the measured ad estimated values i the model i most cases. The egative values of ME showed uderestimatio of the measured values i all cases; therefore, the use of predicted lower miimum temperatures may be more cofidet for frost predictio. The values of F-test for slope ad itercept of liear equatios were ot sigificat i ay of the cases compared with the : lie; therefore, the simple liear regressio equatio i Tables 8 ad 9 showed similarity to : lie. Similarities of liear equatios to : lie showed good predictio of daily early morig miimum temperature. The values of the idex of agreemet (d) ad coefficiet of Nash-Sutcliff (C NS ) i Tables 8 ad 9 idicated that there was a high agreemet betwee the measured ad estimated T mi i Bajgah ad Kooshkak. The most agreemet was i all combiatios for moths. Therefore, it is cocluded that the proposed simple models predicted the daily early morig miimum temperature with acceptable accuracy. 27

11 (a)all moths (b) April (c)may (d)october (e)november (f)december (g) Jauary (h) February (i) March Fig. 5. Compariso of the measured ad estimated T mi by the simple models for validatio i Bajgah. 37

12 (a)all moths (b) April (c)may (d)october (e)november (f)december (g) Jauary (h) February (i) March Fig. 6. Compariso of the measured ad estimated T mi by the simple models for validatio i Kooshkak. Table 8. Liear relatioships betwee the measured (T mm ) ad predicted (T mp ) miimum temperature for differet moths i Bajgah (validatio) Moth Liear equatio R 2 NRMSE MAE ME d C NS F-Test (-) (-) (-) (-) (-) Slope Itercept All T mp =0.92 T mm ** NS NS moths April T mp =0.75 T mm ** NS NS May T mp =0.86 T mm ** NS NS Oct. T mp =0.76T mm ** NS NS Nov. T mp =0.90 T mm ** NS NS Dec. T mp =0.83T mm ** NS NS Ja. T mp =0.66 T mm ** NS NS Feb. T mp =0.72T mm ** NS NS Mar. T mp =0.69 T mm ** NS NS **: Sigificat at % probability level *: NS is o-sigificat 30

13 Table 9. Liear relatioships betwee the measured (T mm ) ad predicted (T mp ) miimum temperature for differet moths i Kooshkak (validatio) Moth Liear equatio NRMSE MAE ME D C NS F-Test (-) (-) (-) (-) (-) Slope Itercept All moths T mp =.02 T mm ** NS NS April T mp =0.73T mm ** NS NS May T mp =0.86 T mm ** NS NS Oct. T mp =0.69 T mm ** NS NS Nov. T mp =0.94 T mm ** NS NS Dec. T mp =0.76 T mm ** NS NS Ja. T mp =0.88 T mm ** NS NS Feb. T mp =0.82 T mm ** NS NS Mar. T mp =0.76 T mm ** NS NS **: Sigificat at % probability level *: NS is o-sigificat R 2 CONCLUSIONS This study proposed a method for forecastig the daily miimum temperature based o the daily dew-poit ad mea relative humidity of the previous day. The daily weather parameters such as wid speed, pa evaporatio, sushie hours ad raifall showed o sigificat effect o the miimum temperature. Istead, parameters such as daily relative humidity ad dewpoit showed a sigificat effect o daily miimum temperature of early morig of the ext day. Simple models were developed to estimate the daily miimum temperature i the ext day usig the dew-poit ad mea relative humidity of the previous day for differet moths ad all combiatios for moths. For the values of mea relative humidity betwee 65 ad 75 % i Bajgah ad 64 ad 66 % i Kooshkak, the daily differece betwee dew-poit ad miimum temperature of the ext day was ear zero i all cases. Therefore, i these rages of relative humidity, the daily miimum temperature is equal to the dew-poit of the previous day. Daily miimum temperature i the ext day was predicted by usig the daily mea relative humidity ad dew-poit i simple regressio models. Daily mea relative humidity ad dew-poit of recet years were used for validatio of the proposed simple models. Daily miimum temperatures were predicted with acceptable accuracy i the validatio of simple models i both areas. REFERENCES Alle, R.G., Pereira, L.S., Raes, D., & Smith, M. (998). Crop Evapotraspiratio. FAO Irrigatio ad Draiage Paper, 56, Bagdoas, A., Georg, J.C., & Gerber, J.F. (978). Techiques of frost predictio ad methods of frost ad cold protectio. World Meteorology Orgaizatio Techology Note, 57. Cary, J.W. (982). Amout of soil ice predicted from weather observatios. Agricultural Meteorology, 27, Didari, S., Zad Parsa, S., Sepaskhah, A.R., Kamgar, A.A., & Khalili, D. (20). Preparatio of frost atlas usig differet iterpolatio methods i a semiarid regio of south of Ira. Theoretical ad Applied Climatology, 08,59-7. Nash, J.E., & Sutcliffe, J.V. (970). River flow forecastig through coceptual models. Joural of Hydrology, 0, Nazemosadat, M.J., Sepaskhah, A.R., & Mohammadi, S. (200). A case study o the relatioship betwee daily dewpoit ad miimum temperature i ext day i Jahrom i Ira. Iraia Joural of Agricultural Sciece ad Techology, 5(3), 9-7. (i Persio) Roseberg, N.J., Blai, L., & Shashi, B. (983). The Biological Eviromet (2 st ed.). Joh Wiley ad Sos. Syder, R.L. (2000). Predictig temperature treds durig freeze ights. Departmet of Lad, Air ad Water Research, Uiversity of Califoria, Davis, CA 9566, USA. Vatskevich, G.Z. (985). Agrometeorology. Traslated from Russia by the Israel Program for Scietific Traslatio for Natioal Sciece Foudatio. Whitema, T.M. (957). Freezig poits of fruits, vegetables, ad florist stocks. Uited States Departmet of Agriculture, 96. Willmott, C.J. (982). Some commets o the evaluatio of model performace. America. Meteoroogy, G3, Ziaee, A.R., Kamgar, A.A., Sepaskhah, A.R., & Rajbar, S. (2006). Determiatio of miimum temperature probability atlas by use of weather parameters i Fars provice i Ira. Iraia Joural of Agricultural Sciece ad Techology, 0(3), (i Persio). 3

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