Analyzing the relationship between geographical elements and precipitation patterns in the southern shores of the Caspian Sea

Document Type : Research Paper

Authors

1 Department of Geography, Yazd University, Yazd, Iran

2 Department of Climatology, Meybod University, Meybod, Iran

Abstract

The present study focuses on the distribution of precipitation in different spatial and temporal patterns based on monthly, seasonal and annual time scales using TRMM data derived from 92 different cells in the south of the Caspian Sea. In addition, to account for the impact of the geographical conditions such as elevation, latitude and longitude on rain values, the Pearson correlation method was used. In terms of the average monthly precipitation in the south of the sea, the results showed that the highest average belonged to November (87 mm), followed by December (74 mm), and finally March and October (67 mm and 66 mm), respectively. The highest negative correlation (0.862) between rain and longitude was observed in autumn at a significant level of 0.01. In addition, the highest negative correlation (0.87) between rain and longitude was found in November at a significant level of 0.01. The maximum annual rain was 892-1305 mm measured in Guilan Province. Precipitation showed a tendency to decline toward the east of Golestan Province, so that the minimum annual precipitation (321-393 mm) was recorded in its western and northeastern parts. The precipitation was positively correlated with elevation and there was a strong inverse relationship between rain and longitude.

Keywords


Ahmadi, M & Narangifard, M 2012, Assessment precipitation regions in Fars Province using TRMM satellite data. Researches in Earth Sciences, 3(11): 28-44.
Akbari Yangehghaleh, M, sanaeinejad, S, Faridhosseini, A & Akbari, M 2018, The study of spatial -temporal distribution of rain, using TRMM data (Case study: Khorasan Razavi Province). Journal of Climate Research, 7: 1-18.
Almazroui, M 2011, Calibration of TRMM rainfall climatology over Saudi Arabia during 1998-2009. Atmospheric Research, 99: 400-414.
Chen, C, Yu, Z, Li, L, & Yang, C 2011, Adaptability evaluation of TRMM satellite rainfall and its application in the Dongjiang River Basin”. Procedia Environmental Sciences, 10: 396-402. DOI: 10.1016/j.proenv. 2011.09.065.
Du, L, Tian, Q, Yu, T, Meng, Q, Jancso, T, Udvardy, P & Huang, Y 2013, A comprehensive drought monitoring method integrating MODIS and TRMM data. International Journal of Applied Earth Observation and Geoinformation, 23: 245-253. doi.org/10.1016/j.jag.2012.09.010.
Duncan, JM, & Biggs, EM 2012, Assessing the accuracy and applied use of satellite-derived precipitation estimates over Nepal. Applied Geography, 34: 626-638. DOI:10.1016/j.apgeog.2012.04.001
Gabella, M, Morin, E, Notarpietro, R & Michaelides, S 2013, Winter precipitation fields in the Southeastern Mediterranean area as seen by the Ku-band Space borne weather radar and two C-band ground-based radars. Atmospheric Research, 119: 120-130.
Huffman, GJ, Bolvin, DT, Nelkin, EJ, Wolff, DB, Adler, RF, Gu, G, Hong, Y, Bowman, KP & Stocker, EF 2007, The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8: 38-55.
Immerzeel, WW, Rutten, MM, & Droogers, P 2009, Spatial downscaling of TRMM precipitation using vegetative response on the Iberian Peninsula. Remote Sensing of Environment, 113: 362-370. DOI:10.1016/j.rse.2008.10.004.
Javanmard, S & Jamli, B J 2015, The study of atmospheric physics parameters over Iran using satellite TRMM-TMI data. Journal of Earth Science & Climatic Change, 6:17. DOI: 10.4172/2157-7617.1000281
Javanmard, S, Yatagai, A, Nodzu, M I, BodaghJamali, J & Kawamoto, H 2010, Comparing high-resolution gridded precipitation data with satellite rainfall estimates of TRMM_3B42 over Iran. Advances in Geosciences, 25: 119-125. DOI: 10.5194/adgeo-25-119-2010.
Jia, S, Zhu, W, Lű, A, & Yan, T 2011, A statistical spatial downscaling algorithm of TRMM precipitation based on NDVI and DEM in the Qaidam Basin of China. Remote sensing of Environment, 115: 3069-3079.
Kaufman, L & Rousseeuw, PJ 2009, Finding groups in data: An introduction to cluster analysis. 344. John Wiley & Sons.
Kummerow, C, Barnes, W, Kozu, T, Shiue, J, Simpson, J 1998, The Tropical rainfall Measuring Mission (TRMM) sensor package. Journal of Atmospheric and Oceanic Technology, 15: 809-817.
Kummerow, C 2000, The status of the Tropical rainfall Measuring Mission (TRMM) after two years in orbit. Journal of Applied Meteorology, 39: 1965-1982.
Li, X H, Zhang, Q, & Xu, C Y 2012, Suitability of the TRMM satellite Precipitation s in driving a distributed hydrological model for water balance computations in Xinjiang catchment, Poyang Lake basin. Journal of Hydrology, 426: 28-38.
Liu, Q, & Fu, Y 2010, Comparison of radiative signals between precipitating and non-precipitating clouds in frontal and typhoon domains over East Asia. Atmospheric Research, 96: 436-446.
Mishra, A K, Gairola, R M, & Agarwal, V K 2012, Rainfall estimation from combined observations using KALPANA-IR and TRMM-precipitation radar measurements over Indian region. Journal of the Indian Society of Remote Sensing, 40: 65-74.
Moazami, S, Golian, S, Kavianpour, M R, & Hong, Y 2013, Comparison of PERSIANN and V7 TRMM Multi-satellite Precipitation Analysis (TMPA) products with rain gauge data over Iran. International Journal of Remote Sensing, 34: 8156-8171. doi.org/10.1080/01431161.2013.833360.
Moffitt, C B, Hossain, F, Adler, R F, Yilmaz, K K, & Pierce, H F 2011, Validation of a TRMM-based global flood detection system in Bangladesh. International Journal of Applied Earth Observation and Geoinformation, 13:165-177.
Mozafari, G A, & Narangifard, M 2015, The vegetative cover deterioration due to the droughts on the Mulla Sadra watershed and application of remote sensing techniques in its monitoring. Water Engineering, 8: 1-14.
Okamoto, K, Miyazaki, S, & Ishida, T 1979, Remote sensing of precipitation by a satellite-borne microwave remote sensor. Acta Astronautica, 6: 1043-1060.
Omidvar, K & Narangifard, M 2015, Study of distribution temporal– spatial the probable maximum precipitation (PMP) in Fars Province. Applied Climatology, 2: 17-36.
Puri, S, Stephen, H, & Ahmad, S 2011, Relating TRMM precipitation radar land surface backscatter response to soil moisture in the southern United States. Journal of Hydrology, 402: 115-125.
Puri, S, Stephen, H, & Ahmad, S 2011, Relating TRMM precipitation radar backscatter to water stage in wetlands. Journal of Hydrology, 401: 240-249.
Roohi, A, Yasin, Z, Kideys, A E, Hwai, A T S, Khanari, A G & Eker‐Develi, E 2008, Impact of a new invasive ctenophore (Mnemiopsis leidyi) on the zooplankton community of the Southern Caspian Sea. Marine Ecology, 29: 421-434.
Shirvani, A & Fakhari Zade Shirazi, E 2014, Comparison of ground based observation of precipitation with TRMM satellite estimations in Fars Province. Journal of Agricultural Meteorology, 2:1-15.
Shrivastava, R, Dash, SK, Hegde, MN, Pradeepkumar, KS & Sharma, DN 2014, Validation of the TRMM multi satellite rainfall product 3B42 and estimation of scavenging coefficients for 131I and 137Cs using TRMM 3B42 rainfall data. Journal of Environmental Radioactivity, 138: 132-136.
Siabi, N, Sanaeinejad, S & Ghahraman, B 2017, Evaluation of rainfall data derived from TRMM satellite, MM5 model and ground observation using sapatio-temporal analysis in arid and semi-arid mountainous area. Geography and Environmental Hazards, 6: 163-179.
Sotodeh, F & Alijani, B 2015, The relationship between spatial distribution of heavy precipitation and pressure patterns in guilan province. Journal of Spatial Analysis Environmental Hazarts, 2: 63-73.
Ud din, S, Al-Dousari, A, Ramdan, A & Al Ghadban, A 2008, Site-specific precipitation estimate from TRMM data using bilinear weighted interpolation technique: An example from Kuwait. Journal of Arid Environments, 72: 1320-1328.
Varikoden, H, Samah, AA & Babu, CA 2010, Spatial and temporal characteristics of rain intensity in the   Peninsular Malaysia using TRMM rain rate. Journal of hydrology, 387: 312-319.