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The Survey of 1 to 5 Day Rainfall in Tehran Province Based on Markof Chain Model Second Stage

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The Survey of 1 to 5 Day Rainfall in Tehran Province Based on Markof Chain Model Second Stage The Survey of 1 to 5 day rainfall in Tehran Province based on Markof Chain model Second stage Dr Mojgan Afshar Iran,Tehran, Azad university, Research & science campus Fardin Saberi Danesh scientail and cultural institute ,Tehran ,Iran InIn TheThe NameName ofof thethe AlmightyAlmighty The Survey of 1 to 5 day rainfall Sequences in Tehran. with the Use of Markov Chain Model second stage The aim of the research: The survey of statistic and synoptic analysis of 1 to 5 day rainfall sequences in Tehran county The research hypothesis: 1-The rainfall in Tehran county has a second stage sequence (that is today rainfall is related to the day before and the day before yesterday. 2-Synoptic patterns have the main role in a couple of days' rainfall sequences in Tehran county. Literature Review World: For the first time, Markov Chain Model was accomplished for the survey of constancy of dry and wet for predicting the rainfall days in Telavive by Gabriel and New mann. (Gabriel and New mann, 1952: 90). Iran the calculation of frequency of dry and wet periods in Babolsar by using Markov of by (Meshkati, 1362: 37) Data and the procedure: 1-Arithmetical Analysis 2- Synoptically analysis Mazandaran karaj QaZvin doushan mehrabad hamand abali aminabad Semnan Centural QOM Figure1: station situations in Tehran province Table 1:feature of research stations TAPE ELEVATION LATITUDE LONGITUDE STATION M N E synoptic 1190/8 35-41 51-19 Tehran mehrabad synoptic 1209/2 35-42 51-20 Doushan tappe synoptic 1312/5 35-55 50-54 karaj synoptic 2465/2 35-45 51-53 Abali rain 1000 35-35 51-28 Aminabad rain 1800 35-39 52-5 Hammand abesard ISLAMIC REPUBLIC OF IRAN (METEOROLOGICAL ORGANIZATION (IRIMO شراب ﻩناﯼلاس دنور 600 500 جرﮎ ﯼلعبﺁ 400 دابﺁ نﯼما 300 ﻩپت ناشود درسبﺁ دنمﻩ 200 نارﻩت 100 0 85 87 89 91 93 95 99 01 03 19 19 19 19 19 19 1997 19 20 20 Figure2:the average rainfall of six cold months in six station in 1985-2004 100 jan 80 feb 60 mar 40 oct 20 nov 0 dec mehrabad doushan karaj abali hamand aminabad Figure3:average monthly rainfall in six stations in 1985-2004 ربتﮎا ﻩام ﮎشخ ﯼا ﻩزور رت ﯼا ﻩزور 600 500 400 300 200 100 0 دابﺁ نﯼما درسبﺁ دنمﻩﯼلعبﺁ جرﮎﻩپت ناشود دابﺁرﻩم ربماون ﻩام ﮎشخ ﯼا ﻩزور رت ﯼا ﻩزور 600 500 400 300 200 100 0 دابﺁ نﯼما درسبﺁ دنمﻩﯼلعبﺁ جرﮎﻩپت ناشود دابﺁرﻩم ربماسد ﻩام ﮎشخ ﯼا ﻩزور رت ﯼا ﻩزور 600 500 400 300 200 100 0 دابﺁ نﯼما درسبﺁ دنمﻩﯼلعبﺁ جرﮎﻩپت ناشود دابﺁرﻩم Figure4 :periods of dry and wet in autumn in six station in 1985-2004 ﻩﯼوناژ ﻩام ﮎشخ ﯼا ﻩزور رت ﯼا ﻩزور 600 500 400 300 200 100 0 دابﺁ نﯼما درسبﺁ دنمﻩﯼلعبﺁ جرﮎﻩپت ناشود دابﺁرﻩم ﻩﯼروف ﻩام ﮎشخ ﯼا ﻩزور رت ﯼا ﻩزور 500 400 300 200 100 0 دابﺁ نﯼما درسبﺁ دنمﻩﯼلعبﺁ جرﮎﻩپت ناشود دابﺁرﻩم سرام ﻩام ﮎشخ ﯼا ﻩزور رت ﯼا ﻩزور 600 500 400 300 200 100 0 دابﺁ نﯼما درسبﺁ دنمﻩﯼلعبﺁ جرﮎﻩپت ناشود دابﺁرﻩم Figure5 :periods of dry and wet in winter in six station in 1985-2004 table 2 ; frequency of sequence of 1 to 5 day rainfall stations Mehrabad Doshan Tappeh Karaj Abali Hamand Aminabad Parameter 0 2650 2642 2650 2258 2629 2984 1 808 816 808 1200 829 474 Σ 3458 3458 3458 3458 3458 3458 0 0 2206 2198 2196 1739 2160 2634 0 1 425 427 438 502 450 328 1 0 423 422 433 499 449 330 1 1 389 396 376 703 384 151 Σ 3438 3438 3438 3438 3438 3438 0 0 0 1830 1830 1823 1359 1801 2329 0 0 1 356 349 357 365 342 281 0 1 0 199 201 214 181 233 222 0 1 1 223 222 218 319 215 106 1 0 0 352 343 352 360 340 284 1 0 1 68 77 79 135 105 46 1 1 0 224 221 219 317 215 107 1 1 1 165 174 157 383 168 44 Σ 3418 3418 3418 3418 3418 3418 0 0 0 0 1 1 1 1 80 85 70 222 77 14 1 1 1 1 1 36 47 35 84 39 4 . Table 3 :the calculation for determining the stage of Markov six cold months in six stations Stations Mehrabad Doshantappeh Karaj َAbali Hamand Aminabad Parameter 0 0/765 0/764 0/766 0/653 0/759 0/862 1 0/235 0/236 0/234 0/347 0/241 0/138 0 0 0/839 0/838 0/834 0/777 0/828 0/889 0 1 0/161 0/162 0/166 0/223 0/172 0/11 1 0 0/521 0/515 0/535 0/415 0/539 0/686 1 1 0/479 0/485 0/465 0/585 0/461 0/314 0 0 0 0/838 0/841 0/837 0/790 0/841 0/894 0 0 1 0/162 0/159 0/163 0/210 0/159 0/106 0 1 0 0/4712 0/475 0/495 0/362 0/520 0/676 0 1 1 0/528 0/525 0/505 0/639 0/480 0/324 1 0 0 0/838 0/816 0/816 0/727 0/764 0/861 1 0 1 0/162 0/184 0/184 0/273 0/236 0/139 1 1 0 0/575 0/560 0/582 0/452 0/561 0/708 1 1 1 0/425 0/440 0/418 548 0/439 0/292 Table 4 :Chi- Squares calculating for determining Markov first stage considering the table Chi-Square Mehrab Doshan Karaj Abali Hamand Amin stations ad Absard Abad month Oct. 67/37 66/70 92/74 86/58 70/76 37/31 Nov. 86/09 295/43 85/65 103/89 102/19 35/36 Dec. 94/83 50/49 66/56 111/80 82/71 39/51 Jan. 67/58 86/68 63/3 75/64 60/38 32/24 Feb. 53/03 51/26 37/58 75/01 39/88 10/49 March 65/82 59/31 50/62 91/43 47/25 53/09 Six cold 296/64 335/74 286/52 538/71 246/05 131/16 months Table 5 : chi- Squares calculating for determining Markov second stage considering the table chi-Square Stations Mehrabad Doshan Karaj Abali Hamand Aminabad month Oct. 20/02 30/16 17/23 32/24 39/13 9/87 Nov. 23/32 6/16 21/49 35/73 2/27 16/73 Dec. 29/32 27/55 52/16 22/52 28/96 18/62 Jan. 29/78 51/84 84/38 29/98 17/36 24/80 Feb. 36/89 30/91 24/19 29/98 26/25 22/30 March 35/03 25/75 31/54 23/57 37/59 21/82 Six cold months 19/69 17/42 21/82 36/06 34/85 14/71 Table 6:The comparison of six cold month observed frequencies with predicted frequencies observed frequencies of 1to 5 day Predicted frequencies of 1 to 5 day sequences sequences parameter 1 2 3 4 5 1 2 3 4 5 station Mehrabad 425 385 165 91 36 430 212 104 49 23 Doshan 427 396 174 85 47 423 208 102 48 23 Karaj 438 376 157 70 35 427 201 94 44 21 Abali 502 703 383 222 84 497 293 170 100 61 Hamand Absard 450 384 168 77 39 446 210 99 46 19 Amin abad 328 151 44 14 4 329 106 35 11 4 Total 2570 2395 1091 559 245 2552 1230 604 298 151 Max 502 703 383 222 84 497 293 170 100 61 Min 328 151 44 14 4 329 106 35 11 4 Synoptically analysis Synoptic analysis of rainfall on 9 th to 13 th of December 1995 as the driest year in Tehran County in 1985-2004 9 december 1995 , the day before rain 10 december 1995 11 december 1995 12 december 1995 13 december 1995 Conclusion - As it was observed, the rain fall in the under study region was not accidentally due to the convection circulations, but it was completely related to the location of immigrant pressure systems. This fact was completely clear in the synoptic analysis. There fore, the synoptic analysis stresses on the use of Markov chain model second stage, for determining the wet and dry periods in under study regions. Suggestions: For organizations, industries, agricultural, reconstructive departments, and so on it is important to predict the weather of their work region for a couple of days, So that they can prevent possible damages. There fore: Markov chain model shows that the prediction through pressure patterns announced by the multimedia can be very helpful for the mentioned organizations and departments. comecome notnot leaveleave thethe worldworld toto thethe badnessbadness ByBy attemptattempt allall togethertogether dodo goodnessgoodness NeverNever cancan remainremain badbad oror goodgood SoSo it'sit's betterbetter toto leaveleave goodnessgoodness asas aa memorialmemorial FerdosiFerdosi.
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