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This paper compares the spatial distribution datasets on monthly precipitation totals derived from the Famine Early Warning System Network FEWS NET service (CHIRPS 2.0 product) and the International Mission of the Global Precipitation Measurement GPM (IMERG v06 product) with ground-based observations of a stationary weather stations located in the steppe region of the Crimean Peninsula in order to assess the representativeness of the precipitation spatial distribution and the applicability of the datasets for water balance calculations and agricultural crop dynamics modeling. A close convergence was observed between the estimated monthly precipitation totals and the precipitation gauge data during the study period (January 2017 - July 2020), with mean correlation coefficients of 0.75 and 0.73 for the GPM IMERG and CHIRPS, respectively. Both products generally overestimated the precipitation values compared to the measured data, with GPM IMERG (final run) exhibiting the greatest overestimations (1.3-2.1 times the weather station values). Our results demonstrate the requirement of GPM-derived precipitation estimations (particularly those from the GPM_3IMERDL v06 daily accumulated late run dataset) to be additionally verified and calibrated based on data from regional weather stations or the CHIRPS 2.0 product (if available).
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Tom
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1--13
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
- Research Institute of Agriculture of Crimea
autor
- Research Institute of Agriculture of Crimea
Bibliografia
- Beck H.E., Pan M., Roy T., Weedon G.P., Pappenberger F., van Dijk A.I.J.M., Huffman G.J., Adler R.F., Wood E.F., 2019, Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS, Hydrology and Earth System Sciences, 23(1), 207-224, DOI: 10.5194/hess-23-207-2019.
- Chen S., Zhang L., Zhang Y., Guo M., Liu X., 2020, Evaluation of Tropical Rainfall Measuring Mission (TRMM) satellite precipitation products for drought monitoring over the middle and lower reaches of the Yangtze River Basin, China, Journal of Geographical Sciences, 30, 53-67, DOI: 10.1007/s11442-020-1714-y.
- Chokngamwong R., Chiu L.S., 2008, Thailand daily rainfall and comparison with TRMM products, Journal of Hydrometeorology, 9, 256-66, DOI: 10.1175/2007JHM876.1.
- Dembélé M., Zwart S.J., 2016, Evaluation and comparison of satellite-based rainfall products in Burkina Faso, West Africa, International Journal of Remote Sensing, 37(17), 3995-4014, DOI: 10.1080/01431161.2016.1207258.
- Dinku T., Funk C., Peterson P., Maidment R., Tadesse T., Gadain H., Ceccato P., 2018, Validation of the CHIRPS satellite rainfall estimates over eastern of Africa, Quarterly Journal of the Royal Meteorological Society, 144(51), 292-312, DOI: 10.1002/qj.3244.
- Ebert E.E., Janowiak J.E., Kidd C., 2007, Comparison of near real-time precipitation estimates from satellite observations and numerical models, Bulletin of the American Meteorological Society, 88(1), 47–64, DOI: 10.1175/BAMS-88-1-47.
- Funk C.C., Peterson P.J., Landsfeld M.F., Pedreros D.H., Verdin J.P., Rowland J.D., Romero B.E., Husak G.J., Michaelsen J.C., Verdin A.P., 2014, A quasi-global precipitation time series for drought monitoring, U.S. Geological Survey Data Series, 832, DOI: 10.3133/ds832.
- Funk C., Verdin J., Michaelsen J., Peterson P., Pedreros D., Husak G., 2015, A global satellite-assisted precipitation climatology, Earth System Science Data, 7, 275-287, DOI: 10.5194/essd-7-275-2015.
- Hou A.Y., Kakar R.K., Neeck S., Azarbarzin A.A., Kummerow C.D., Kojima M., Oki R., Nakamura K., Iguchi T., 2014, The global precipitation measurement mission, Bulletin of the American Meteorological Society, 95, 701-722, DOI: 10.1175/BAMS-D-13-00164.1.
- Huffman G., Bolvin D., Nelkin E., Wolff D., Adler R., Gu G., Hong Y., Bowman K. P., Stocker E., 2007, The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales, Journal of Hydrometeorology, 8, 38-55, DOI: 10.1175/JHM560.1.
- Karthikeyan L., Pan M., Wanders N., Kumar D.N., Wood E.F., 2017, Four decades of microwave satellite soil moisture observations: Part 2. Product validation and inter-satellite comparisons, Advances in Water Resources, 109, 236-252, DOI: 10.1016/j.advwatres.2017.09.010.
- Kidd C., Levizzani V., Turk J., Ferraro R., 2009, Satellite precipitation measurements for water resource monitoring, Journal of the American Water Resources Association, 45(3), 567-579, DOI: 10.1111/j.1752-1688.2009.00326.x.
- Liu C., Zipser E.J., 2015, The global distribution of largest, deepest, and most intense precipitation systems, Geophysical Research Letters, 42(9), 3591-3595, DOI: 10.1002/2015GL063776.
- Liu J., Duan Z., Jiang J., Zhu A., 2015, Evaluation of three satellite precipitation products TRMM 3B42, CMORPH, and PERSIANN over a subtropical watershed in China, Advances in Meteorology, 2015, DOI: 10.1155/2015/151239.
- Liu Z., Ostrenga D., Teng W., Kempler S., 2012, Tropical Rainfall Measuring Mission (TRMM) precipitation data and services for research and applications, Bulletin of the American Meteorological Society, 1317-1325, DOI: 10.1175/BAMS-D-11-00152.1.
- Nashwan M., Shahid S., Wang X., 2019, Assessment of satellite-based precipitation measurement products over the hot desert climate of Egypt, Remote Sensing, 11(5), DOI: 10.3390/rs11050555.
- Ning S., Wang J., Jin J., Ishidaira H., 2016, Assessment of the latest GPM-era high-resolution satellite precipitation products by comparison with observation gauge data over the Chinese mainland, Water, 8(11), DOI: 10.3390/w8110481.
- Pang J., Zhang H., Xu Q., Wang Yujie, Wang Y., Zhang O., Hao J., 2020, Hydrological evaluation of open-access precipitation data using SWAT at multiple temporal and spatial scales, Hydrology and Earth System Science, 24, 3603-3626, DOI: 10.5194/hess-24-3603-2020.
- Paredes-Trejo F.J., Barbosa H.A., Kumar T.L., 2017, Validating CHIRPS-based satellite precipitation estimates in Northeast Brazil, Journal of Arid Environment, 139, 26-40, DOI: 10.1016/j.jaridenv.2016.12.009.
- Retalis A., Katsanos D., Tymvios F., Michaelides S., 2018, Validation of the first years of GPM operation over Cyprus, Remote Sensing, 10(10), 1520, DOI: 10.3390/rs10101520.
- Saeidizand R., Sabetghadam S., Tarnavsky E., Pierleoni A., 2018, Evaluation of CHIRPS rainfall estimates over Iran, Quarterly Journal of the Royal Meteorological Society, 144(51), 282-291, DOI: 10.1002/qj.3342.
- Satgé F., Ruelland D., Bonnet M. P., Molina J., Pillco R., 2019, Consistency of satellite-based precipitation products in space and over time compared with gauge observations and snow-hydrological modelling in the Lake Titicaca region, Hydrology and Earth System Science, 23(1), 595-619, DOI: 10.5194/hess-23-595-2019.
- Scheel M.L., Rohrer M., Huggel C., Villar D.S., Silvestre E., Huffman G.J., 2011, Evaluation of TRMM multi-satellite precipitation analysis (TMPA) performance in the Central Andes region and its dependency on spatial and temporal resolution, Hydrology and Earth System Science, 15(8), 2649-2663, DOI: 10.5194/hess-15-2649-2011.
- Tang G., Clark M.P., Papalexiou S.M., Ma Z., Hong Y., 2020, Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets, Remote Sensing of Environment, 240, DOI: 10.1016/j.rse.2020.111697.
- Villarini G., Mandapaka P.V., Krajewski W.F., Moore R.J., 2008, Rainfall and sampling uncertainties: A rain gauge perspective, Journal of Geophysical Research, 113(D11), DOI: 10.1029/2007JD009214.
- Wang C., Tang G., Han Z., Guo X., Hong Y., 2018, Global intercomparison and regional evaluation of GPM IMERG Version- 03, Version-04 and its latest Version-05 precipitation products: similarity, difference and improvements, Journal of Hydrology, 564, 342-356, DOI: 10.1016/j.jhydrol.2018.06.064.
- WMO, 2008, Guide to hydrological practices. Volume I. Hydrology - From measurement to hydrological information, 6th edition, WMO-No. 168, World Meteorological Organization, Geneva, available at http://www.wmo.int/pages/prog/hwrp/publications/guide/english/168_Vol_I_en.pdf (data access 10.08.2020).
- Xiao S., Xia J., Zou L., 2020, Evaluation of multi-satellite precipitation products and their ability in capturing the characteristics of extreme climate events over the Yangtze River basin, China, Water, 12(4), DOI: 10.3390/w12041179.
- Yee M.S., Walker J.P., Rüdiger C., Parinussa R.M., Koike T., Kerr Y.H., 2017, A comparison of SMOS and AMSR2 soil moisture using representative sites of the OzNet monitoring network, Remote Sensing of Environment, 195, 297-312, DOI: 10.1016/j.rse.2017.04.019.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-71d702a0-a3fc-4e7b-aaa8-a152d6ee42de