Analysis of anomalies and perceptible water cycles in Iran atmosphere

Document Type : Full length article

Authors

1 Associate Professor in Climatology Department of Geography University of Zanjan –Zanjan- Iran

2 PhD. Student of climatology - Zanjan University Zanjan –Zanjan- Iran

3 Associate Professor in metrological Iranian

Abstract

Extended Abstract
Introduction
Water vapor is considered to be one of more significant atmospheric constituents as it contributes in precipitation and is also a critical element of the climate system. This climate element extended from earth surface to upper level of troposphere that potentially precipitable. Accordingly it called perceptible water. Therefore The total atmospheric water vapor contained in a vertical column of unit cross-sectional area extending between any two specified levels, commonly expressed in terms of the height to which that water substance would stand if completely condensed and collected in a vessel of the same unit cross section. The total perceptible water is that contained in a column of unit cross section extending all of the way from the earth's surface to the “top” of the atmosphere.
The water vapor component of air requires monitoring because of its importance to weather and climate and the essential role it plays in the operation of the global water cycle. This is the reason that atmospheric perceptible water determines the potential value of precipitation as well as an index for forecast precipitation for a certain time of year. So it is an important variable in climatic study and climate change survey.
Precise calculation of perceptible water needs to know about the atmospheric water vapor amount. However the amount of water vapor is determined by many factors including atmospheric density, temperature, cloudiness, wind direction and velocity, humidity in top of geographical situation. All of these factors determine the capacity of humidity, distances from the water bodies as well as leading the water vapor to any location.
In this paper it has attempted to calculate perceptible water in atmospheric column from the earth's surface to the top of troposphere. This purposeful effort has been done to achieve the long term trends of precipitable water over Iran atmosphere. In order to accede this purpose the NCEP/NCAR data has been applied.
Data and Methods
Consider a column of liquid water with cross-sectional area, and certain height. This height is the perceptible water. One way to determining the mass of water vapor (in grams) in a vertical column one square centimeter in cross-sectional area that extends from Earth's surface to the upper reaches of the atmosphere. Mathematically, if x(p) is the specific humidity at the pressure level, p, then the perceptible water vapor, PW, contained in a layer bounded by pressures p1 and p2 is given by

Where g refers to gravity acceleration.
For the purposes of our study, the pressure and specific humidity of NCEP/NCAR which exist for each 6 hours has been used. This data characterized by 2.5 longitude*2.5 latitude degree resolution.
In order to find out what we had decided to find, many software including Grads, Surfer and Matlab have been used. So at first general characters including mean and coefficient of variation of percipitable water has been mapped. Then the trends maps have been represented. In addition we have used sequential Man-Kendal method to diagnosing trends during the time sequence.
To find the cause and the result of this trends, humidity advection and long term change in temperature as well as precipitation over Iran has calculated.
Discussion
The mean of precipitable water in Iran is about 14.3 mm. According to coefficient of variation, the most stationary amount of the mean is at 18:00 o’clock meanwhile the most non stationary take place at 06:00 o’clock. Central Iran which located in dry region as well as far from water bodies, it contains much more precipitable water in compare to Zagros mountain chain. The most precipitable water as well as lowest coefficient of variation is happened in Caspian Sea coast as well as Persian Gulf coasts. In general mountains area has experienced more variation in compare with law areas.
In regard for trend analyses, spatial distribution of daily trends has been mapped in fig 1. As it is clear almost all over Iran (except in Bandar Abass and Chabahar) decreasing significant trend by -0.000043 to -0.000067 mm/day especially in south as well as southwest of the country has been occurred.


Fig 1: Spatial distribution of precipitable water over Iran (Mm/day)

In order to survey temporal variation and base on Man-Kendal test has been used. The result is displayed in fig 2. As it is clear since the first year under investigation, trend had decreasing behavior, while it beams significant in 1987.

Fig 2: Trend changes in precipatable water over Iran Using Man-Kendal Sequential test
These trends caused by decreasing in water vapor advection also result in increasing in temperature in addition to decreasing of precipitation over Iran.
Conclusion
Surveying precipitable water over Iran has shown that this climatic parameter is dramatically depending on local as well as global factors. Accordingly the most spatial variations take place in 00:00 and 06:00 o’clock.
Trends analyses have shown decreasing significant trend by -0.000043 to -0.000067 mm/day in the country.

Keywords

Main Subjects

References

جهانبخ ، س. و عدالت دوست، م. ) 1387 (. تغییر اقلیم در ایران )مطالعة موردی: راخص نوسانات اطلس رمالی به یناوان راخصای از
تأایرات فعالیت خورریدی بر تغییرات بارش آذربایجان(. سومین کنفرانس مدیریت منابع آب ایران، دانشگاه تبریز .چتفیلد، سی. ) 1381 (. مقدمه ای بر تجزیه و تحلیل سری های زمانی. ترجمة حسنعلی نیرومند و ابوالقاسم بزرگ نیا، انتشارات فردوسی مشهد.
عساکره، ح. ) 1388 (. تحلیل همسازه ها سری های زمانی دمای سالانة تبریز. تحقیقات جغرافیایی، شمارة 93 ، 33 - 50 .
علیجانی، ب. و کاویانی، م. ر. ) 1385 (. مبانی آب و هواشناسی. انتشارات دانشگاه تهران.
مسعودیان، ا.، عساکره، ح.، محمدی، ب. و حلبیان، ا. ح. ) 1391 (. نمایش و پردازش داده های جوی. انتشارات دانشگاه اصفهان.
Alijani, B., Kaviani, M. (2006). Foundations of climate .Tehran University Press.
Asakereh, H. (2009). Harmonic analysis of time series of annual temperature .Tabriz Geographical Research, No. 93, pp. 33-50 .
Asakereh, H., Razmi, R. (2011). Analysis of annual rainfall variations in the North West of Iran .Geography and Planning, No. 3, pp. 162-147.
Asakereh, H., Doostkamian M. (2013). Temporal and spatial changes in atmosphere water precipitation in Iran .
Accepted in Journal of Iran Water Resources Management.
Azad, S., Vigneshb, T.S. and Narasimha, R. (2009). Periodicities in Indian Monsoon rainfall over spectrally homogeneous regions. Int. J. Climatology, DOI: 10.1002/joc.2045.
Carvalho, A.A., Toni’s, C., Jones, H.R., Rocha and Polito, P.S. (2007). Anti-persistence in the global temperature anomaly field, Vol. 14. pp 723 – 733.
Chatfield, C. (2002 .)Introduction to time series analysis, translated by hasanali niromand and abouhghasem bozorgnia .Publisher of Mashhad.
Chen, M., Dickinson, R.E., Zen,g X., Hahmann, A.N. )1996(. Comparison of precipitation observed over the continental United States to that simulated by a climate model. Journal of Climate, Vol. 9, pp 2233–2249.
Collier, J.C., Bowman, K.P. )2004(. Diurnal cycle of tropical precipitation in a general circulation model. Journal of Geophysical Research, Vol. 109, pp 1-20.
Dai, JAN A., Trenberth, K.E. (2004). The diurnal cycle and its depiction in the Community Climate System Model. Journal of Climate, Vol, 17(5): 930–951.
Garcia, J.A., Serrano, A. and Gallego, M.Cruz (2002). A spectral analysis of Iberian peninsula monthly rainfall Theory. Application Climatological, Vol. 71, pp 77-95.
Hadjimitsis, Z., Metrical, I., Gazing, A., Retails, Chrysoulakis, N. and Michael Ides, S. (2011). Estimation of spatiotemporal distribution of perceptible water using MODIS and AVHRR data: a case study for Cyprus. Adv. Geosci. Vol 30, pp 23–29.
Hartmann, S. Becker, and King, L. (2008). Quasi-periodicities in Chinese precipitation time series Theory. Appl. Climatology. 92, pp 155–163.
Jahanbakhash, S., Edalat Doust, M. (2008 .)Climate Change in Iran (Case Study: the North Atlantic Oscillation index as an indicator of the effects of solar activity on the rainfall variations Azerbaijan .)Iran Water Resources Management Conference, Tabriz University.
Kalaycı Serdar, M., Cagatay Karabork, Ercan Kahya, (2004). Analysis of el-Niño signal on Turkish stremlow and precipitation pattern using spectral analysis. Fresenius Environmental Bulletin, Volume 13(8).
Kaneual, R.P. and Teixeira, N.R. (1991). Power spectrum analysis of the annual rainfall series for massachusetts (NE. U.S.A), Climatic Change, 18: 89-94.
Kerns, B.W.J., Chen, Y.L., Chang, M.Y. (2010). The diurnal cycle of winds, rain, and clouds over Taiwan during the meaty, summer, and autumn rainfall regimes. Monthly Weather Review, Vol, 2, pp 497–516
Kristin K. and Graf, B. (2008). Global positioning system (GPS) perceptible water in forecasting lightning at spaceport canaveral. Weather forecasting, vol 23, pp. 219 – 232.
Lana, M.D., Martinez, C. Serra, and Burguen, A. (2005), Periodicities and irregularities of indices describing the daily pluviometric regime of the Fabre Observatory (NE Spain) for the years 1917–1999 Theory. Application Climatological, Vol. 82, pp 183–198.
Lee, M.I., Schubert, S.D., Suarez, M.J., Held, I.M., Lau, N.C., Plushy, J.J., Kumar, A., Kim, H.K., Schema, J.K.E. (2007). An analysis of the warm-season diurnal cycle over the continental United States and northern Mexico in general circulation models. J. Hydrometeor 8(3): 344–366.
Masoodian, Syed A., Asakereh, H., Hossain M., Halabian A. (2012 .)Processing weather data .Isfahan University Press.
Mathieu Rouault, A.B., Shouraseni Sen Roy C and Robert C. Balling Jr, (2012). Short communication: The diurnal cycle of rainfall in South Africa in the austral summer, Int. J. Climatology. vol. 10, pp. 1 -8.
Nesbitt, S., Zipser, E. (2003). The diurnal cycle of rainfall and convective intensity according to three years of TRMM measurements. Journal of Climate, Vol. 16, pp 1456-1475.
Parameswaran, K. and Krishna Murthy, B.V. )1990(. Altitude profiles of tropospheric water vapor at low latitudes. J. App. Meteoric. Vol. 29, 665 – 679.
Pritchard M.S. and Somerville, R.C.J. (2008). Scripps institution of oceanography. University of California, San Diego, Mail Code 0224, 9500 Gilman Drive, La Jolla, CA 92093-0224.
Surcel, M., Berenguer, M., Zawadzki (2010(. The diurnal cycle of precipitation from continental radar mosaics and numerical weather prediction models. Part I: Methodology and seasonal comparison. Review monthly weather, Vol. 138, pp 3084–3106.
Tingley, Martin P. (2012). A Bayesian ANOVA Scheme for Calculating Climate Anomalies, with Applications to the Instrumental Temperature Record. J. Climate, Vol. 25, 777–791.
Towards, R. (2007). Seasonal characteristics of diurnal precipitation variation in Krakow (south Poland). International Journal of Climatology, Vol. 27(7), pp 957–968.
Vasic, S., Lin, C., Zawadzki, I., Bousquet, O., Chaumont, D. (2007). Evaluation of precipitation from numerical weather prediction models and satellites using values retrieved from radars. Monthly Weather Review, Vol. 135, pp 3750–3766.
Qian, A. Qin (2008). Precipitation division and climate shift in China from 1960 to 2000, Monsoon and Environment Research Group, School of Physics, Peking University, Beijing, China, Vol. 9, pp 1 -17.
Wallace, J. (1975(. Diurnal variations in precipitation and thunder storm frequency over the conterminous United States. Monthly Weather Review, 103(5), pp. 406–419.
Yang, G., Slinger, J., (2001). The diurnal cycle in the tropics. Review Monthly weather, Vol 129, pp 784-801.
Yun-Ju, J. and Lee, J.Y. (2010). Time series analysis of hydrologic data obtained from a man-made undersea LPG cavern, Engineering Geology, Vol. 113, pp. 70–80.
Physical Geography Research
Volume 46, Issue 4 - Serial Number 4
January 2015
Pages 435-444

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History

  • Receive Date: 22 July 2013
  • Revise Date: 16 April 2014
  • Accept Date: 27 August 2014

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