Zależności Z-R dla różnych typów opadów jako narzędzie do radarowego szacowania wielkości opadów = The Z-R relationships for different types of precipitation as a tool for radar-based precipitation estimation

Barszcz, Mariusz Paweł; Stańczyk, Tomasz; Brandyk, Andrzej

doi:0033-2143 (print)

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Zależności Z-R dla różnych typów opadów jako narzędzie do radarowego szacowania wielkości opadów = The Z-R relationships for different types of precipitation as a tool for radar-based precipitation estimation Barszcz, Mariusz PawełStańczyk, TomaszBrandyk, Andrzej

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Przegląd Geograficzny T. 95 z. 2 (2023)

Barszcz, Mariusz Paweł : Autor ; Stańczyk, Tomasz : Autor ; Brandyk, Andrzej : Autor

laser disdrometer ; reflectivity and intensity of precipitation ; Z-R relationship ; meteorological radar ; hydrology

An alternative to the use of rain gauges as sources of precipitation data is provided by laser disdrometers, which inter alia allow for high-temporal-resolution measurement of the reflectivity (Z) and intensity (R) of precipitation. In the study detailed here, an OTT Parsivel1 laser disdrometer located at the Meteorological Station of Warsaw University of Life Sciences (SGGW) generated the 95,459 Z-R data pairs recorded across 1-min time intervals that were subject to further study. Included values for the reflectivity and instantaneous intensity of precipitation were found to be in the respective ranges of -9.998‑67.898 dBZ and 0.004‑153.519 mm h−1 (given that values for precipitation intensity below 0.004 mm h−1 were excluded from further consideration). The material obtained covered the months from April to October in the years 2012‑2014 and 2019‑2020 (30 months in total), which were selected for the study due to the completeness of data. The measured reflectivity and intensity data for precipitation were used to establish the relationship pertaining between the two (by reference to descriptive parameters a and b), with such results considered to contribute to the improved calibration of meteorological radars, and hence to more-accurate radar-based estimates of amounts of precipitation. The Z-R relationship as determined for all measurement data offered a first step in the research process, whose core objective was nevertheless to determine separate Z-R relationships for datasets on rain, rain with snow (sleet), and snow (given that precipitation in the form of hail did not occur during the surveyed measurement periods). That said, it is important to note that only a few Polish studies have in any way involved disdrometer-based measurement of precipitation reflectivity and intensity, as well as the relationships between these aspects. In the event, the Z-R relationships obtained for the measurement sets were characterised by high values for coefficients of correlation (in the range 0.96‑0.97) and determination, as well as low values for the root mean-square error (ranging from 0.29 to 0.34). Statistics point to a good fit of the Z-R relationships (regression lines) to the specified datasets. Values noted for parameter a (the multiplier in the power-type Z-R relationship) were seen to differ significantly in relation to rain, rain with snow, and snow, being of 285.56, 76.07 and 914.74 respectively. In contrast, values noted for parameter b (the exponent) varied only across the narrow range of 1.47‑1.62. The obtained research results for parameter a indicate the need to consider Z-R relationships matched to specific types of precipitation in the data processing procedure of radar data. This could increase the accuracy of estimating precipitation amounts using radars belonging to the nationwide POLRAD system. The relationships Z = 285.56R1.47 for rainfall (as the dataset’s dominant type of precipitation), as well as Z = 293.76R1.46 for all data, proved highly similar to the classic relationship obtained for convective rainfall by Hunter (1996), as given by Z = 300R1.4. On the other hand, the values of the a parameter in the Z-R relationships fond for the two datasets proved to be much larger than those in the model developed by Marshall and Palmer (1948), which took the form Z = 200R1,6 and has been the relationship used in Poland as radar images are created.

Atlas, D. & Chmela, A.C. (1957). Physical-synoptic variations of drop-size parameters. W: Preprints, sixth weather radar conference (s. 21‑19). Boston, MA: American Meteorological Society.
Amengual, A. (2022). Hydrometeorological analysis of the 12 and 13 September 2019 widespread flash flooding in eastern Spain. Natural Hazard and Earth System Sciences, 22, 1159‑1179. https://doi/org/10.5194/nhess-22-1159-2022
Berne, A., Delrieu, G., Creutin, J.-D., & Obled, C. (2004). Temporal and spatial resolution of rainfall measurements required for urban hydrology. Journal of Hydrology, 299(3‑4), 166‑179.
Biniak-Pieróg, M., Biel, G., Szulczewski, W., & Żyromski, A. (2015). Evaluation of methods of comparative analysis of sums of atmospheric precipitation measured with the classical method and with a contact-less laser rain gauge. Annals of Warsaw University of Life Sciences - SGGW Land Reclamation, 47, 371‑382. https://doi/org/10.1515/sggw-2015-0038
Biniak-Pieróg, M. (2017). Monitoring of atmospheric precipitation and soil moisture as basis for the estimation of effective supply of soil profile with water. Monografie 207. Wrocław: Wydawnictwo Uniwersytetu Przyrodniczego.
Bouilloud, L., Delrieu, G., Boudevillain, B., & Kirstetter, P.-E. (2010). Radar rainfall estimation in the context of post-event analysis of flash-flood events. Journal of Hydrology, 394(1‑2), 17‑27. https://doi/org/10.1016/j.jhydrol.2010.02.035
Bournas, A. & Baltas, E. (2022). Determination of the Z-R Relationship through Spatial Analysis of X-Band Weather Radar and Rain Gauge Data. Hydrology, 9, 137. https://doi/org/10.3390/hydrology9080137
Burszta-Adamiak, E. (2012). Analysis of Stormwater Retention on Green Roofs/Badania Retencji Wód Opadowych Na Dachach Zielonych. Archives of Environmental Protection, 38, 3‑13. https://doi/org/10.2478/v10265-012-0035-3
Chumchean, S., Sharma, A., & Seed, A. (2003). Radar rainfall error variance and its impact on radar rainfall calibration. Physics and Chemistry of the Earth, 28(1‑3), 27‑39. https://doi/org/10.1016/S1474-7065(03)00005-6
Conti, F.L., Francipane, A., Pumo, D., & Noto, L.V. (2015). Exploring single polarization X-band weather radar potentials for local meteorological and hydrological applications. Journal of Hydrology, 531, 508‑522. https://doi/org/10.1016/j.jhydrol.2015.10.071
Delrieu, G., Bonnifait, L., Kirstetter, P.-E., & Boudevillain, B. (2014). Dependence of radar quantitative precipitation estimation error on the rain intensity in the Cévennes region, France. Hydrological Sciences Journal, 59(7), 1308‑1319.
Dotzek, N. & Beheng, K.D. (2001). The influence of deep convective motions on the variability of Z-R relations. Atmospheric Research, 59, 15‑39. https://doi/org/10.1016/S0169-8095(01)00107-7
Gualco, L.F, Campozano, L., Maisincho, L., Robaina, L., Muñoz, L., Ruiz-Hernández, J.C., Villacís, M., & Condom, T. (2021). Corrections of Precipitation Particle Size Distribution Measured by a Parsivel OTT2 Disdrometer under Windy Conditions in the Antisana Massif, Ecuador. Water, 13, 2576. https://doi.org/10.3390/w13182576
Gunn, K.L.S. & Marshall, J.S. (1958). The distribution with size of aggregate snowflakes. Journal of Meteorology, 15, 452‑461.
Guyot, A., Pudashine, J., Protat, A., Uijlenhoet, R., Pauwels, V.R.N., Seed, A., & Walker, J.P. (2019). Effect of disdrometer type on rain drop size distribution characterization: a new dataset for Southeastern Australia. Hydrol. Earth Syst. Sci., 23, 4737‑4761. https://doi/org/10.5194/hess-23-4737-2019
Hazenberg, P., Yu, N., Boudevillain, B., Delrieu, G., & Uijlenhoet, R. (2011). Scaling of raindrop size distributions and classification of radar reflectivity- rain rate relations in intense Mediterranean precipitation. Journal of Hydrology, 402, 179‑192. https://doi/org/10.1016/j.jhydrol.2011.01.015
He, X., Sonnenborg, T.O., Refsgaard, J.C., Vejen, F., & Jensen, K.H. (2013). Evaluation of the value of radar QPE data and rain gauge data for hydrological modeling. Water Resources Research, 49(9), 5989‑6005. https://doi/org/10.1002/wrcr.20471
Hunter, S. (1996). WSR-88D radar rainfall estimation: capabilities, limitations and potential improvements. National Weather Digest, 20(4), 26‑36.
Jaffrain, J. & Berne. A. (2011). Experimental quantification of the sampling uncertainty associated with measurements from PARSIVEL disdrometers. Journal of Hydrometeorology, 12, 352‑370. https://doi/org/10.1175/2010JHM1244.1
Jakubiak, B., Licznar, P., & Malinowski, Sz.P. (2014). Rainfall estimates from radar vs. raingauge measurements. Warsaw case study. Environment Protection Engineering, 40(2), 159‑170. https://doi/org/10.5277/epel140212
Jiang, Y., Yang, L., Zeng, Y., Tong, Z., Li, J., Liu, F., Zhang, J., & Liu, J. (2022). Comparison of summer raindrop size distribution characteristics in the western and central Tianshan Mountains of China. Meteorological Applications, 29(3), e2067. https://doi/org/10.1002/met.2067
Johannsen, L.L., Zambon, N., Strauss, P., Dostal, T., Neumann, M., Zumr, D., Cochrane, T.A., Blöschl, G., & Klik, A. (2020). Comparison of three types of laser optical disdrometers under natural rainfall conditions. Hydrological Sciences Journal, 65(4), 524‑535. https://doi/org/10.1080/02626667.2019.1709641
Joss, J. & Waldvogel, A. (1970). A method to improve the accuracy of radar-measured amounts of precipitation, In: Preprints, 14th Radar Meteorology Conference (s. 237‑238). Tucson, AZ: American Meteorological Society.
Jwa, M., Jin, H-G., Lee, J., Moon, S., & Baik, J-J. (2020). Characteristics of Raindrop Size Distribution in Seoul, South Korea According to Rain and Weather Types. Asia-Pacific Journal of Atmospheric Sciences, 57(3), 605‑617. https://doi/org/10.1007/s13143-020-00219-w
Krajewski, W.F., Kruger, A., Caracciolo, C., Golé, P., Barthes, L., Creutin, J-D., Delahaye, J-Y., Nikolopoulos, E.I., Ogden, F., & Vinson, J-P. (2006). DEVEX-Disdrometer Evaluation Experiment: Basic results and implications for hydrologic studies. Advances in Water Resources, 29, 311‑325. https://doi/org/10.1016/j.advwatres.2005.03.018
Licznar, P. (2009). Wstępne wyniki porównawczych testów polowych elektronicznego deszczomierza wagowego OTT Pluvio2 i disdrometru laserowego Parsivel. Instal, 7/8, 43‑50.
Licznar, P., & Krajewski, W.F. (2016). Precipitation Type Specific Radar Reflectivity-rain Rate Relationship for Warsaw, Poland. Acta Geophysica, 64(5), 1840‑1857.
Licznar, P., & Siekanowicz-Grochowina, K. (2015). Wykorzystanie disdrometru laserowego do kalibracji obrazów pochodzących z radarów opadowych na przykładzie Warszawy. Ochrona Środowiska, 37(2), 11‑16.
Marshall, J.S. & Palmer, W.McK. (1948). The distribution of raindrops with size. Journal of Meteorology, 5, 165‑166. http://doi.org/10.1175/1520-0469(1948)005<0165:TDORWS>2.0.CO; 2
Marshall, J.S., Hitschfeld, W., & Gunn, K.L.S. (1955). Advances in radar weather. Advances in Geophysics, 2, 1‑56. https://doi/org/10.1016/S0065-2687(08)60310-6
Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Bingner, R.L., Harmel, R.D., & Veith, T.L. (2007). Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 50(3), 885‑900. https://doi/org/10.13031/2013.23153
Moszkowicz, S., & Tuszyńska, I. (2006). Meteorologia radarowa. Podręcznik użytkownika informacji radarowej IMGW. Warszawa: Instytut Meteorologii i Gospodarki Wodnej.
Szewrański, S. (2009). Rozbryzg jako forma erozji wodnej gleb lessowych. Monografie 78. Wrocław: Wydawnictwo Uniwersytetu Przyrodniczego we Wrocławiu.
Thorndahl, S., Einfalt, T., Willems, P., Nielsen, J.E., Veldhuis, M.-C., Arnbjerg-Nielsce, K., Rasmussen, M.R., & Molnar, P. (2017). Weather radar rainfall data in urban hydrology. Hydrology and Earth System Sciences, 21, 1359‑1380.
Thurai, M., Petersen, W.A., Tokay, A., Schultz, C., & Gatlin, P. (2011). Drop size distribution comparisons between Parsivel and 2-D video disdrometers. Advances in Geosciences, 30, 3‑9. https://doi/org/10.5194/adgeo-30-3-2011
Tokay, A., Peterson, W.A., Gatlin, P., & Wingo, M. (2013). Comparison of raindrop size distribution measurements by collocated disdrometers. Journal of Atmospheric and Oceanic Technology, 30(8), 1672‑1690. https://doi/org/10.1175/JTECH-D-12-00163.1
Tokay, A., Wolff, D.B., & Petersen, W.A. (2014). Evaluation of the new version of the laser-optical disdrometer, OTT Parsivel2. Journal of Atmospheric and Oceanic Technology, 31, 1276‑1288. https://doi/org/10.1175/JTECH-D-13-00174.1
Villarini, G. & Krajewski, W.F. (2010). Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall. Surveys in Geophysics, 31(1), 107‑129. https://doi/org/10.1007/s10712-009-9079-x