Mariusz Paweł Barszcz

Articles

Variability of the Z-R relationship in monthly periods – to increase the accuracy of estimating the amount of precipitation using meteorological radars

Mariusz Paweł Barszcz

Przegląd Geograficzny (2024) tom 96, zeszyt 4, pp. 447-458 | Full text
doi: https://doi.org/10.7163/PrzG.2024.4.2

Further information

Abstract

The amount of precipitation in a catchment is the basic quantity used in modeling hydrological phenomena. So far, precipitation data has been most often obtained from rain gauges, which enable the measurement of only point amount of precipitation. An alternative to the use of rain gauges as a source of precipitation data is provided by meteorological radars, which provide data with high‑spatial resolution. However, radar measurement of precipitation are not accurate enough because it is an indirect measurement. Radars measure reflectivity, which, based on a specific Z-R relationship (i.e. between the values for reflectivity and intensity of precipitation), is converted into the amount of precipitation. The main limitation in the estimation of precipitation using radars is attributed to the high variability of the Z-R relationship in time and space. Disdrometers, which enable the determination of the Z-R relationship on the basis of the reflectivity and intensity of precipitation, are of fundamental importance to the improved calibration of meteorological radars.

Measurements of reflectivity and precipitation intensity, carried out at the Meteorological Station of Warsaw University of Life Sciences using the Parsivel1 laser disdrometer, were the basis for the determination of the relationships between these quantities (parameters a and b for the Z-R relationship) for each individual month (in the April‑October periods) in the years 2012‑2014 and 2019‑2020.

The values of the a parameter for the Z-R relationship determined as a result of the research significantly differed for individual months. They ranged from 199 to 493, and their arithmetic mean was 311. Moreover, the values of the a parameter varied considerably for corresponding months in different years. On the other hand, the values of the b parameter were within a narrow range, i.e. from 1.30 to 1.56, with the mean value of 1.45. The determined values of the a and b parameters were consistent with those found in the literature. The range of the variability of the b parameter was so small that its uncertainty can be perceived as insignificant. These results suggest that assuming a constant value for parameter b is justified, meaning the variability of the ZR relationship can be accounted for solely by changes in parameter a. This simplifies the implementation of the Z-R relationship in the operational work of a meteorological radar. The results of these studies indicate the need to take into account the variable values of the a parameter for the Z-R relationship in relation to various monthly periods in the radar data processing procedure. However, it is necessary to carry out analyses that will allow to assess the impact of such activities on increasing the accuracy of estimating the amount of precipitation using meteorological radars.

The maximum individual values of the a parameter were recorded in July, August and October. Whereas, the highest mean values of the a parameter, calculated on the basis of its values for the corresponding months in the years 2012‑2014 and 2019‑2020, were obtained for data sets from June, July and August. This means that the highest values of this parameter generally occurred in periods with frequent convective precipitation. In the current research, an attempt was made to link the values of the a parameter for individual months (determined separately for 30 months) with the values of basic statistical measures (including the maximum and arithmetic mean), which were calculated on the basis of instantaneous values of reflectivity and intensity of precipitation for the relevant months. It was fund that there is a strong correlation between the values of the a parameter for Z-R relationship for individual months and the mean monthly reflectivity (expressed in mm6 m−3 units) – the correlation coefficient is R = 0.70. The obtained relationship between these quantities requires verification in terms of its suitability for the calibration of radar images.

Keywords: laser disdrometer, reflectivity and precipitation intensity, Z-R relationship, meteorological radar cali- bration, precipitation amount, hydrology

Mariusz Paweł Barszcz [mariusz_barszcz@sggw.edu.pl], Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Instytut Inżynierii Środowiska

Citation

APA: Barszcz, M. (2024). Zmienność zależności Z-R w okresach miesięcznych – dla zwiększenia dokładności szacowania wielkości opadów za pomocą radarów meteorologicznych. Przegląd Geograficzny, 96(4), 447-458. https://doi.org/10.7163/PrzG.2024.4.2
MLA: Barszcz, Mariusz Paweł. "Zmienność zależności Z-R w okresach miesięcznych – dla zwiększenia dokładności szacowania wielkości opadów za pomocą radarów meteorologicznych". Przegląd Geograficzny, vol. 96, no. 4, 2024, pp. 447-458. https://doi.org/10.7163/PrzG.2024.4.2
Chicago: Barszcz, Mariusz Paweł. "Zmienność zależności Z-R w okresach miesięcznych – dla zwiększenia dokładności szacowania wielkości opadów za pomocą radarów meteorologicznych". Przegląd Geograficzny 96, no. 4 (2024): 447-458. https://doi.org/10.7163/PrzG.2024.4.2
Harvard: Barszcz, M. 2024. "Zmienność zależności Z-R w okresach miesięcznych – dla zwiększenia dokładności szacowania wielkości opadów za pomocą radarów meteorologicznych". Przegląd Geograficzny, vol. 96, no. 4, pp. 447-458. https://doi.org/10.7163/PrzG.2024.4.2

Analysis of maximum rainfall amounts from the PMAXTP model, and their application in verifying the performance of an urban drainage system

Mariusz Paweł Barszcz, Ewa Kaznowska, Michał Wasilewicz

Przegląd Geograficzny (2024) tom 96, zeszyt 4, pp. 473-494 | Full text
doi: https://doi.org/10.7163/PrzG.2024.4

Further information

Abstract

Accurate determination of amounts of rainfall in a catchment area, in the context of duration and exceedance probability, forms the basis for the design and verification of drainage (sewerage) systems in cities, and for stormwater management based on hydrodynamic models. Existing rainfall models are the ones used most commonly in supplying simulation models. The development and implementation of PMAXTP models by Poland’s Institute of Meteorology and Water Management (IMGW-PIB) in 2022 (based on rainfall data from 100 rain gauges from the period 1986-2015), covering the entire territory of Poland, has ensured free access to current and reliable information regarding local maximum amounts of rainfall (unit intensities).

This study presents the results of analyses comparing rainfall amounts with specific characteristics (durations ranging from 5 to 4320 minutes and probabilities from 2 to 50%), as determined using the probabilistic PMAXTP model for the Warsaw-Bielany Meteorological Station, as set against corresponding values from the Błaszczyk and Bogdanowicz-Stachý models used commonly in Poland. Given doubts cited in the study as regards correctness of method and data, it is advisable to extend support to a position presented by various researchers, that the Błaszczyk model for the design of sewer systems be discontinued. On the other hand, in general the maximum amounts of rainfall (quantiles) from the probabilistic PMAXTP model for the Warsaw-Bielany Station are seen to exhibit lower values as compared with corresponding data from the prob abilistic Bogdanowicz-Stachý model (for the central region), for rainfall durations ranging from 15 to 1440 minutes, and for all assumed levels of probability of rainfall. The differences between amounts of rainfall predicted by the two models do achieve significance in some cases. The authors also found that the amounts of rainfall considered from the PMAXTP model in relation to the upper confidence interval are also lower than the corresponding values from the Bogdanowicz-Stachý model, where rainfall duration is in the 15- to 720-minute range (denoting the values used most commonly in practice). In such a situation, use of the PMAXTP model for the Warsaw-Bielany Station in the designing of a sewer system would generally suggest lower diameters of pipe than would the values obtained using the Bogdanowicz-Stachý model. The advice is thus for the modelling of drainage systems for other areas of Poland to first compare amounts of rainfall from the PMAXTP model with data from other (including local) rainfall models. Our analyses also included verification as to the spatial variability of rainfall from the PMAXTP models, in relation to the performance of the sewer system in the area around Warsaw’s Chopin Airport. Equally, corresponding values were found to be similar in a comparison of amounts of rainfall suggested by the PMAXTP model for one of that project’s 100 measurement stations (i.e. Warsaw-Bielany) and the synoptic Warsaw-Okęcie Station (approximately 13 km away, and located within the studied catchment area of Warsaw’s Potok Służewiecki) – in this case determined through interpolation of data from measurement stations. The studied catchment area of 17.8 km² was also found to be characterized by minimal variability in the quantile values for rainfall with the rainfall event considered (p=20%, t=15 min).

However, significant differences in amounts of rainfall generated by the PMAXTP models are to observed between the Warsaw-Bielany and Świder measurement stations, located about 27 km apart. The quantile rainfall amounts for the Świder Station exceed the corresponding upper confidence-interval rainfall values for the Warsaw-Bielany Station. These differences in rainfall confirm that the use of local maximum-rainfall models in designing sewer systems is justified. Hydrodynamic simulations in the SWMM model determined that choice of rainfall models adopted impacted significantly on maximum values for flows in the catchment studied. The flows obtained under the catchment loading with the Bogdanowicz-Stachý model are substantially greater than those from the PMAXTP model; while the value obtained in response to rainfall using the Błaszczyk model stands out significantly. Information was further obtained concerning overloads in specific stormwater drains in the vicinity of Chopin Airport, as well as rainwater overflows from that area’s network of drains. All of this denotes the wisdom and justification of the hydraulic efficiency of systems of sewers and drains being verified using a hydrodynamic model.

Keywords: PMAXTP rainfall model, Bogdanowicz-Stachý model, Błaszczyk model, maximum rainfall, SWMM hydrodynamic model, stormwater sewer system

Mariusz Paweł Barszcz [mariusz_barszcz@sggw.edu.pl], Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Instytut Inżynierii Środowiska
Ewa Kaznowska [ewa_kaznowska@sggw.edu.pl], Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Instytut Inżynierii Środowiska
Michał Wasilewicz [michal_wasilewicz@sggw.edu.pl], Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Instytut Inżynierii Środowiska

Citation

APA: Barszcz, M., Kaznowska, E., & Wasilewicz, M. (2024). Analiza wysokości opadów maksymalnych z modelu PMAXTP i ich zastosowanie do weryfikacji działania miejskiego systemu odwodnienia. Przegląd Geograficzny, 96(4), 473-494. https://doi.org/10.7163/PrzG.2024.4
MLA: Barszcz, Mariusz Paweł, et al. "Analiza wysokości opadów maksymalnych z modelu PMAXTP i ich zastosowanie do weryfikacji działania miejskiego systemu odwodnienia". Przegląd Geograficzny, vol. 96, no. 4, 2024, pp. 473-494. https://doi.org/10.7163/PrzG.2024.4
Chicago: Barszcz, Mariusz Paweł, Kaznowska, Ewa, and Wasilewicz, Michał. "Analiza wysokości opadów maksymalnych z modelu PMAXTP i ich zastosowanie do weryfikacji działania miejskiego systemu odwodnienia". Przegląd Geograficzny 96, no. 4 (2024): 473-494. https://doi.org/10.7163/PrzG.2024.4
Harvard: Barszcz, M., Kaznowska, E., & Wasilewicz, M. 2024. "Analiza wysokości opadów maksymalnych z modelu PMAXTP i ich zastosowanie do weryfikacji działania miejskiego systemu odwodnienia". Przegląd Geograficzny, vol. 96, no. 4, pp. 473-494. https://doi.org/10.7163/PrzG.2024.4

The Z-R relationships for different types of precipitation as a tool for radar-based precipitation estimation

Mariusz Paweł Barszcz, Tomasz Stańczyk, Andrzej Brandyk

Przegląd Geograficzny (2023) tom 95, zeszyt 2, pp. 149-162 | Full text
doi: https://doi.org/10.7163/PrzG.2023.2.2

Further information

Abstract

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 h1 (given that values for precipitation intensity below 0.004 mm h1 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, 776.07 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 ZR 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.

Keywords: laser disdrometer, reflectivity and intensity of precipitation, Z-R relationship, meteorological radar, hydrology

Mariusz Paweł Barszcz [mariusz_barszcz@sggw.edu.pl], Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Instytut Inżynierii Środowiska
Tomasz Stańczyk [tomasz_stanczyk@sggw.edu.pl], Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Instytut Inżynierii Środowiska
Andrzej Brandyk [andrzej_brandyk@sggw.edu.p], Centrum Wodne

Citation

APA: Barszcz, M., Stańczyk, T., & Brandyk, A. (2023). Zależności Z-R dla różnych typów opadów jako narzędzie do radarowego szacowania wielkości opadów. Przegląd Geograficzny, 95(2), 149-162. https://doi.org/10.7163/PrzG.2023.2.2
MLA: Barszcz, Mariusz Paweł, et al. "Zależności Z-R dla różnych typów opadów jako narzędzie do radarowego szacowania wielkości opadów". Przegląd Geograficzny, vol. 95, no. 2, 2023, pp. 149-162. https://doi.org/10.7163/PrzG.2023.2.2
Chicago: Barszcz, Mariusz Paweł, Stańczyk, Tomasz, and Brandyk, Andrzej. "Zależności Z-R dla różnych typów opadów jako narzędzie do radarowego szacowania wielkości opadów". Przegląd Geograficzny 95, no. 2 (2023): 149-162. https://doi.org/10.7163/PrzG.2023.2.2
Harvard: Barszcz, M., Stańczyk, T., & Brandyk, A. 2023. "Zależności Z-R dla różnych typów opadów jako narzędzie do radarowego szacowania wielkości opadów". Przegląd Geograficzny, vol. 95, no. 2, pp. 149-162. https://doi.org/10.7163/PrzG.2023.2.2

Assessment of the suitability of the laser disdrometer and meteorological radar for rainfall estimation

Mariusz Paweł Barszcz

Przegląd Geograficzny (2022) tom 94, zeszyt 4, pp. 451-470 | Full text
doi: https://doi.org/10.7163/PrzG.2022.4.3

Further information

Abstract

Contemporary challenges in the management of stormwater and modelling of rainfall-runoff processes (in urban areas in particular) require the use of rainfall-estimation devices more advanced than rain gauges. One such device is the laser disdrometer, which allows (alongside radar reflectivity) for measurement of the intensity of rainfall of high temporal resolution and an accuracy greater than that available using rain gauges. On the other hand, meteorological radar makes it possible to estimate rainfall with a high degree of spatial resolution. The disadvantage of radar observations is the inaccuracy of the rainfall data obtained.

Measurements of atmospheric precipitation conducted at the WULS-SGGW Meteorological Station in Warsaw in the years 2012‑2014 and 2019‑2020, using a tipping-bucket rain gauge and the laser disdrometer (Parsivel), were combined with data obtained from the meteorological radar in Legionowo (in the C-band), with this allowing data to be collected to allow for assessment of the usefulness of the disdrometer and radar where the estimation of rainfall is concerned. The two instruments have independent systems by which to record precipitation data, ensuring a mutual time shift. This made temporary synchronisation a necessity.

The data for the entire study period were used in analysing correlations between 24‑hour rainfall depths estimated on the basis of the rain gauge, on the one hand; and the disdrometer on the other. The correlation coefficient R obtained was equal to 0.87. However, the total amount of rainfall calculated on the basis of the data from the disdrometer was about 40% greater than the corresponding value from the rain gauge.

From the dataset for the years 2012‑2014, 21 individual events were selected for further analysis, with these being ones for which radar-estimated rainfall data in the form of a PAC hydrological product generated by the system belonging to Poland’s Institute of Meteorology and Water Management (IMGW-PIB) were also available. The data measured using the rain gauge and the disdrometer were characterised by a high time resolution, of 1 min. The rainfall-intensity values obtained from the PAC product had a temporal resolution of 10 min and a spatial resolution of 1 km. The rainfall data from the disdrometer and radar were then used in analysing the correlations between these and corresponding measurements made by rain-gauge. The mean and median values of the R correlation coefficient, obtained in these analyses on the basis of rainfall-intensity values averaged over 10-min time intervals (though observed at the basic 1-min resolution) were, when estimated using the disdrometer, of 0.98 and 0.99 respectively. Correlations based around rainfall-intensity values at the 1-min level of resolution only assumed lower values. The adequate values of the R coefficient, as determined for the radar data, were of 0.68 and 0.77 respectively.

The study also extended to include comparison of total values estimated for 21 individual rainfall events using the disdrometer and radar (the PAC hydrological product), as compared with data measured using the rain gauge. The analysed values from the disdrometer were greater than the corresponding rain-gauge values for almost all events, while those obtained using radar were lower in most cases. The mean and median values of the relative error, obtained in relation to the values of rainfall totals measured using the disdrometer, were 35.2 and 38.3% respectively. The relative error values, obtained in adequate analysis based around data from the PAC radar product, proved to be much higher, and amounted to 49.1 and 59.1% respectively. This analysis therefore made it clear how disdrometer- and radar-based data require prior correction before any potential use can be made of them, e.g. in hydrological analyses.

This paper’s simple method of adjusting the heights of rainfall estimated on the basis of the disdrometer at specific (assumed 10-min) time intervals during the event was able to achieve a significant reduction of differences in the total rainfall values for single events, as supplied by data from the disdrometer and the rain gauge. In regard to the adjusted data from the disdrometer, the mean and median values for relative error were of 15.5 and 17.6% respectively, in respect of the 12 rainfall events used to verify the method.

Keywords: tipping-bucket rain gauge, laser disdrometer, meteorological radar, hydrology, rainfall intensity and totals, correlation of rainfall data

Mariusz Paweł Barszcz [mariusz_barszcz@sggw.edu.pl], Szkoła Główna Gospodarstwa Wiejskiego w Warszawie, Instytut Inżynierii Środowiska

Citation

APA: Barszcz, M. (2022). Ocena przydatności disdrometru laserowego i radaru meteorologicznego do szacowania wielkości opadów deszczu. Przegląd Geograficzny, 94(4), 451-470. https://doi.org/10.7163/PrzG.2022.4.3
MLA: Barszcz, Mariusz Paweł. "Ocena przydatności disdrometru laserowego i radaru meteorologicznego do szacowania wielkości opadów deszczu". Przegląd Geograficzny, vol. 94, no. 4, 2022, pp. 451-470. https://doi.org/10.7163/PrzG.2022.4.3
Chicago: Barszcz, Mariusz Paweł. "Ocena przydatności disdrometru laserowego i radaru meteorologicznego do szacowania wielkości opadów deszczu". Przegląd Geograficzny 94, no. 4 (2022): 451-470. https://doi.org/10.7163/PrzG.2022.4.3
Harvard: Barszcz, M. 2022. "Ocena przydatności disdrometru laserowego i radaru meteorologicznego do szacowania wielkości opadów deszczu". Przegląd Geograficzny, vol. 94, no. 4, pp. 451-470. https://doi.org/10.7163/PrzG.2022.4.3