Estimation of precipitation using PERSIANN-CDR and CMC-based satellite productions (Case study: upstream of the Zayandehroud dam)

Document Type : Research Article


1 Department of Civil Engineering, Faculty of civil engineering and transportation, University of Isfahan

2 Surveying and Geomatics Engineering Department , Faculty of civil engineering and transportation, University of

3 Department of Civil Engineering, Faculty of civil engineering and transportation, University of Isfahan, Isfahan


Precipitation and its measurement by rain and snow gauges are mostly important data for water resources management. However, measuring these data has limitations due to both temporal and spatial resolutions. By developing the SRE (Satellite-based Rainfall Estimates) datasets, assessment, evaluation, and comparison of SREs datasets against in-situ observations in different parts of Glob, also Iran is developed in various studies. In this study, by selecting the upstream area of the Zayandehroud Dam as the case study, two datasets, PERSIANN-CDR (PERSIANN-Climate Data Record) and Canadian Meteorological Center (CMC) Daily Snow Depth Analysis Data, are selected to evaluate their performance for the estimation of two variables of rainfall and snow water equivalent (SWE) in the period 1999 to 2019, respectively. The performance of these two SREs using in-situ gauges (a total of 16 rain gauges and 14 SWE gauges) in the upstream area of the Zayandehroud Dam on a monthly time scale is evaluated. For this purpose, different evaluation indices of the correlation coefficient, mean square root of error, and relative error are used. In addition, the performance of SREs in precipitation detection is examined using the classification statistics. Based on the obtained results, the correlation coefficient of 0.48 and relative error of 54.55% indicates that the estimated rainfall amounts by PERSIANN-CDR are in the upper-estimation condition over the study area. Also, the evaluation CMC-based SWE estimations show that the best Amounts SWE is estimated with an error of 4.22% and the highest correlation (CC) is 0.34.


[1]. Dinku T, Ceccato P, Grover KE, Lemma M, Connor SJ, Ropelewski CF. Validation of satellite rainfall products over East Africa's complex topography. International Journal of Remote Sensing. 2007; 28(7):1503-1526.
[2]. Ashouri H, Hsu KL, Sorooshian S, Braithwaite DK, Knapp KR, Cecil LD, Nelson BR, Prat OP. PERSIANN-CDR: daily precipitation climate data record from multi-satellite observations for hydrological and climate studies. Bulletin of the American Meteorological Society. 2014; 96(1): 69–84.
[3]. Beck HE, van Dijk HA, Levizzani V, Schellekens J, Miralles DG, Martens B, Roo A. MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data. Hydrology and Earth System Science. 2017; 21: 589-615.
[4]. Alijanian M, Rakhshandehroo GR, Mishra AK, Dehghani M. Evaluation of remotely sensed precipitation estimates using PERSIANN-CDRand MSWEP for spatio-temporal drought assessment over Iran. Journal of Hydrology. 2019; 579: 124189.
[5]. Smith T, Arkin P, Bates J, Huffman J. Estimating Bias of Satellite-Based Precipitation Estimates. Journal of Hydrometeorology. 2006; 7(5): 841-856.
[6]. Tian Y., et al., Component analysis of errors in satellitebased precipitation estimates. Journal of Geophysical Research. 2009. 114: D24101.
 [7]. Lockhoff M, Zolina O, Simmer C, Schulz J. Evaluation of Satellite-Retrieved Extreme Precipitation over Europe using Gauge Observations. Journal of Climate. 2014; 27: 607-623.
[8]. Musie M, Sen S, Srivasatva P. Comparison and evaluation of gridded precipitation datasets for streamflow simulation in data scarce watersheds of Ethiopia. Journal of Hydrology. 2019; 579:124168
[9]. Xiang Y, Chen J, Li L, Peng T; Yin Z, Evaluation of Eight Global Precipitation Datasets in Hydrological Modeling. Remote Sensing. 2021; 13(14): 2831.
[10]. Noor M, Ismail T, Shahid S, Asaduzzaman M, Dewan A. Evaluating intensity-duration-frequency (IDF) curves of satellite-based precipitation datasets in Peninsular Malaysia. Atmospheric Research. 2021; 248:105203
[11]. Javanmard S, Yatagai1 A, Nodzu MI, BodaghJamali J, Kawamoto H. Comparing high-resolution gridded precipitation data with satellite rainfall estimates of TRMM 3B42 over Iran. Advances in Geosciences. 2010. 25: 119–12.
 [12]. Moazami S, Golian S, Kavianpour MR, Hong Y. Comparison of PERSIANN and V7 TRMM Multi-satellite Precipitation Analysis (TMPA) products with rain gauge data over Iran. Internatinal Journal of Remote Sensing. 2013. 34:8156-8171.
 [13]. Katiraie-Boroujerdy PS, Nasrollahi N, Hsu KL, Sorooshian S. Evaluation of satellite-based precipitation estimation over Iran. Journal of Arid Environments. 2013; 97: 205-219.
[14]. Alijanian M, Rakhshandehroo GR, Mishra AK, Dehghani M. Evaluation of Satellite Rainfall Climatology using CMORPH, PERSIANN-CDR, PERSIANN, TRMM, MSWEP over Iran. International Journal of Climatology. 2017; 37: 4896-4914.
[15]. Saeidizand R, Sabetghadam S, Tarnavsky E, Pierleoni A. Evaluation of CHIRPS rainfall estimates over Iran. Quarterly Journal of the Royal Meteorological Society. 2018; 144: 282-291
[16]. Jafari SM, Nikoo MR, Dehghani M, Alijanian, M. Evaluation of two satellite-based products against ground-based observation for drought analysis in the southern part of Iran. Natural Hazards. 2020; 102: 1249-1267.
[17]. Abbasi N, Opp C, Ribbe L, Baez-Villanueva OM, Besalatpour A. Evaluation of Five Rainfall Estimate Products Over Different Climatic Zones in The Zayandehrud River Basin. Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS), Tunis, Tunisia, 2020; 265-268.
[18]. Hosseini-Moghari SM, Tang Q. Validation of GPM IMERG V05 and V06 Precipitation Products over Iran. Journal of Hydrometeorology. 2020; 21(5): 1011-1037.
[19]. Keikhosravi Kiany MS, Massodian SA, Balling RC, Darand M. Evaluation of TRMM 3B43, GPM IMERG, CHIRPS, and ERA5 Data in Estimating Precipitation and Capturing Meteorological Droughts over Iran. International Journal of Climatology. 2021.[In press].
[20]. Beaumont P. (1974). Water resource development in Iran. Geographical Journal. 1974; 140 (3): 418-431.
 [21]. Tabaei M, Ayoubi S, Aghaei A. Early Holocene Paleoenvironmental changes in North of Gavkhouni Swamp- East of Isfahan-Iran: a review of evidence from palynology. Geopersia. 2019; 9(1): 81-87
[23]. Beck HE, et al., Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, satellite precipitation measurement, 2020; 69: 625–653.
[24]. Sturm M, Holmgren J, Liston G.E. A Seasonal Snow Cover Classification System for Local to Global Applications. Journal of Climate. 1995; 8: 1261–1283.
[26]. Tan ML, Ibrahim AL, Duan Z, Cracknell AP, Chaplot V. Evaluation of Six High-Resolution Satellite and Ground-Based Precipitation Products over Malaysia. Remote Sensing. 2015; 7: 1504-1528.
[27]. Mashingia F, Mtalo F, Bruen M. Validation of remotely sensed rainfall over major climatic regions in Northeast Tanzania. Physics and Chemistery of the Earth. 2014; 67–69: 55–63.
[28]. Levizzani V, Laviola S, Cattani E. Detection and measurement of snowfall from space. Remote Sensing. 2011; 3: 145–166.
[29]. Yong B, et al., The first evaluation of the climatological calibration algorithm in the real-time TMPA precipitation estimates over two basins at high and low latitudes. Water Resources Research. 2013; 49: 2461–2472.
[30]. Habib E, Henschke A, Adler R. Evaluation of TMPA satellite-based research and real-time rainfall estimates during six tropical related heavy rainfall events over Louisiana, USA. Atmospheric Research. 2009; 94 (3): 373-388.
[31]. Sorooshian S, Hsu KL, Gao X, Gupta HV, Imam B, Braithwaite D. Evaluation of PERSIANN system satellite-based estimates of tropical rainfall. Bulletin of the American Meteorological Society. 2000; 81: 2035–2046.
[32]. Katiraie-Boroujerdy PS, Nasrollahi N, Hsu KL, Sorooshian S. Evaluation of satellite-based precipitation estimation over Iran. Journal of Arid Environments. 2013; 97: 205-219.
Volume 9, Issue 1
April 2022
Pages 157-172
  • Receive Date: 29 August 2021
  • Revise Date: 03 October 2021
  • Accept Date: 26 February 2022
  • First Publish Date: 21 March 2022