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Due to the important hydrological and meteorological significance, the performance of different kinds of precipitation products for the Tibetan Plateau (TP) has been evaluated in previous studies. However, the performance of the products on a high spatial-temporal scale has not been clearly shown. Based on the Chinese Meteorological Administration (CMA) ground rain gauge observations during 2017–2018 over the TP, this paper analyzes the multi-scale performance of four satellite-based datasets (IMERG_Uncal, IMERG_Cal, GSMaP_MVK, and GSMaP_Gauge), two reanalysis datasets (ERA5 and ERA5-L), and one multi-source merged dataset (CMFD) for different precipitation intensities with a special attention to the characterization of spatiotemporal variability of heavy precipitation. Firstly, this study examines how the quality of precipitation products varies with time scale and precipitation intensity. CMFD generally shows the best quality and has the most stable quality at all temporal scales. Satellite products perform better in summer while reanalysis products show better results in cold seasons. Another significant issue is the impact of gauge-based calibration. GSMaP_Gauge with daily-scale gauge calibration is often considered to outperform other products. However, our study finds that GSMaP_Gauge is problematic at smaller spatiotemporal scales, especially in capturing heavy precipitation. The long-term performance of multi spatiotemporal scale comparison of different precipitation products is the focus of this study, which can help with their application and improvement. • CMFD has more stable quality at different spatial and temporal scales and precipitation intensities. • Satellite precipitation estimates can better describe heavy precipitation in summer over the TP, while reanalysis precipitation estimates show better performance in cold seasons. • In poorly gauged areas, gauged-based calibration may not necessarily improve the quality of precipitation products. [ABSTRACT FROM AUTHOR]

Abstract: A Local Area Weather Radar (LAWR) is an X-band weather radar developed to meet the needs of high resolution rainfall data for hydrological applications. The LAWR system and data processing methods are reviewed in the first part of this paper, while the second part of the paper focuses on calibration. The data processing for handling the partial beam filling issue was found to be essential to the calibration. LAWR uses a different calibration process compared to conventional weather radars, which use a power-law relationship between reflectivity and rainfall rate. Instead LAWR uses a linear relationship of reflectivity and rainfall rate as result of the log transformation carried out by the logarithmic receiver as opposed to the linear receiver of conventional weather radars. Based on rain gauge data for a five month period from a dense network of nine gauges within a 500×500m area and data from a nearby LAWR, the existing calibration method was tested and two new methods were developed. The three calibration methods were verified with three external gauges placed in different locations. It can be concluded that the LAWR calibration uncertainties can be reduced by 50% in two out of three cases when the calibration is based on a factorized 3 parameter linear model instead of a single parameter linear model. [Copyright &y& Elsevier]

Abstract: The WMO Field Intercomparison of Rainfall Intensity (RI) Gauges started on October, 1st 2007 at Vigna di Valle (Italy) and was concluded in May 2009. Those catching type instruments, out of the selected rain gauges based on various measuring principles, and the four rain gauges selected as reference instruments to be installed in a pit, were preliminarily calibrated in the laboratory before their final installation at the Field Intercomparison site. The recognized WMO laboratory at the University of Genoa was involved in this task, using the same standard tests adopted for the previously held WMO Laboratory Intercomparison of RI gauges. Further tests were performed to investigate the one-minute performance of the involved instruments. The present paper deals with basically Tipping-Bucket Rain gauges (TBRs) and Weighing Gauges (WGs), using results from tests performed under constant flow rates in laboratory conditions. The objective of this initial phase of the Intercomparison was to single out the counting errors associated with each instrument, so as to help the understanding of the measured differences between instruments in the field during the second phase. Results and comments on the preliminary laboratory calibration exercise are reported in this paper together with their implications for the analysis of the outcome of the Intercomparison in the Field. [Copyright &y& Elsevier]

Abstract: Estimation of the radar reflectivity from Local Area Weather Radars (LAWR) is investigated. Normally, the LAWR system operates with the Dimensionless Radar Output (DRO) instead of dBZ, because the absolute scaling to dBZ is unknown for the LAWR. A transformation methodology is proposed for LAWR DRO–dBZ conversion. The method applies dBZ observations from ground based disdrometers. The paper illustrates the possibility of establishing a direct relationship between the LAWR DRO estimates and the physical radar reflectivity of the precipitation. Also, rain intensity estimate from the LAWR system, by means of the Marshall–Palmer relation, is conducted nonlinearly from the DRO estimate. This diverges from prior investigations and applications of the LAWR system, which typically rely on a linear assumption between the rain intensity and the LAWR DRO. [Copyright &y& Elsevier]

Abstract: The spaceborne weather radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite can be used to adjust Ground-based Radar (GR) echoes, as a function of the range from the GR site. The adjustment is based on the average linear radar reflectivity in circular rings around the GR site, for both the GR and attenuation-corrected NearSurfZ TRMM Precipitation Radar (TPR) images. In previous studies, it was found that in winter, for the lowest elevation of the Cyprus C-band radar, the GR/TPR equivalent rain rate ratio was decreasing, on average, of approximately 8dB per decade. In this paper, the same analysis has been applied to another C-band radar in the southeastern Mediterranean area. For the lowest elevation of the “Shacham” radar in Israel, the GR/TPR equivalent rain rate ratio is found to decrease of approximately 6dB per decade. The average departure at the “reference”, intermediate range is related to the calibration of the GR. The negative slope of the range dependence is considered to be mainly caused by an overshooting problem (increasing sampling volume of the GR with range combined with non-homogeneous beam filling and, on average, a decreasing vertical profile of radar reflectivity). To check this hypothesis, we have compared the same NearSurfZ TPR images versus GR data acquired using the second elevation. We expected these data to be affected more by overshooting, especially at distant ranges: the negative slope of the range dependence was in fact found to be more evident than in the case of the lowest GR elevation for both the Cypriot and Israeli radar. [Copyright &y& Elsevier]

Abstract: The aim of the paper is to study the validation and correction of the Convective Rainfall Rate (CRR) algorithm, which utilises three channels from Meteosat Second Generation to estimate rainfalls: IR 10.8μm, WV 6.2μm and VIS 0.6μm. The original CRR algorithm was applied to data from Central Europe (the Czech Republic) but since the calibration matrices (which are the core of CRR) were previously derived using data from Spain and Norway, we recalculated these matrices using data from the Czech Republic. We found that the original and the new matrices were significantly different in absolute values and in the values of IR 10.8μm, WV 6.2μm and VIS 0.6μm under which rainfalls were observed. We subjectively modified these calculated calibration matrices and used them within the CRR algorithm. We also complemented the algorithm with the correction of the distribution of estimated rainfalls. All three methods, the original and our two algorithms, were compared according to various categorical measures and other statistical measures (like Root Mean Square Error). The results showed that the new calibration matrices, complemented by the distribution correction, yielded more accurate rainfall estimates than the other two methods. [Copyright &y& Elsevier]

Abstract: Application of weather radar data in urban hydrology is evolving and radar data is now applied for both modelling, analysis, and real time control purposes. In these contexts, it is all-important that the radar data is well calibrated and adjusted in order to obtain valid quantitative precipitation estimates. This paper presents some of the challenges in small marine X-band radar calibration by comparing three calibration procedures for assessing the relationship between radar and rain gauge data. Validation shows similar results for precipitation volumes but more diverse results on peak rain intensities. [Copyright &y& Elsevier]

Abstract: This paper is a comparative study between the two most common hailpad calibration systems: one annual calibration of a whole consignment of material, and the individual calibration of each plate after a hailfall. Individual calibration attempts to minimize errors due to differences in sensitivity to the impact of hailstones between plates from the same consignment, or due to differences in the inking process before the actual measurement. The comparison was carried out using calibration data from the past few years in the hailpad network in south-western France, and data from an individual calibration process on material provided by the hailpad network in Lleida (Spain). The same type of material was used in the two cases. The results confirm that the error in measuring hailstone sizes is smaller in the case of an individual calibration of hailpads than when one single calibration process was carried out for a whole consignment. The former is approximately 80% of the latter. However, this error could have been higher if it had not been the same person carrying out the single calibration process and the measuring of the dents: it has been found that differences in the inking process may account for up to 20% of the error in the case of small hailstones. Calibration errors affecting other variables, e.g. energy or parameter λ of the exponential size distribution are generally higher (5% and 18%, respectively) than errors due to the spatial variability of the hailstones. However, the calibration method does not influence the maximum size, since the relative error attributed to the spatial variability is about 8 times the calibration error. In conclusion, if errors in determining energy or parameter λ are to be reduced to a minimum, it is highly advisable to be consistent in applying the measuring procedure (if possible with the same person carrying out the measurements all the time), and even to use individual calibration on each plate, always bearing in mind that technicians have to be trained appropriately in order to achieve the highest possible degree of uniformity. [Copyright &y& Elsevier]

Abstract: In this paper setup, operational problems and a straightforward calibration approach for a cost-effective X-Band radar are presented. The LAWR (Local Area Weather Radar) system is based on conventional ship radar technology which is adapted to register rainfall within a range of about 60 km with a spatial resolution of 500 m per pixel. The instrument offers neither Doppler processing nor vertical scan capabilities but uses 20° wide (vertical) beam. The calibration suffers from an unfavorably distributed and very sparse rain gauge network, heavy clutter contamination of the signal and obstructions by surrounding terrain. A specific scaling approach is developed, that includes satellite data on cloud frequency and distribution, to overcome these limitations. Observed clutter is removed and missing values are replaced by bilinear interpolation of the undisturbed signals. A temporal and spatial bias of the radar signal is corrected using an omni-directional spatial distribution hypothesis. This is possible because of the location of the radar site in the transition zone between high rainfall on the eastern Andean slopes and low rainfall on the leeward side. A further limitation of the system is that the LAWR does not provide information on the measured reflectivity Z but dimensionless counts (8 bit resolution). Calibration is performed assuming a linear relation between radar output and rainfall as recommended by the systems manufacturer. The intercomparison of rain gauge and scatterometer data with calibrated radar rainfall reveals a good performance of the developed calibration approach. [Copyright &y& Elsevier]

Abstract: The Institute of Urban Water Management and Landscape Water Engineering of the Graz University of Technology (Austria) operates a hydrological research area in the City of Graz. In this urban research area precipitation and runoff data are collected by order of the municipality of Graz. At present precipitation data are measured by seven tipping bucket rain gauges. Comparative measurements have shown a deviation between the recorded and the actual precipitation intensity. This made the institute calibrate the rain gauges periodically. In the middle of the 1990s, the development of a field calibration kit was started. Based on the experiences with the first field calibration kit, a microprocessor controlled device was developed. With this calibration device, the tipping bucket rain gauges are calibrated at regular intervals. In this paper the calibration process and the current results for seven rain gauges are discussed. The calibration process is dynamic calibration and uses a peristaltic pump. Not all of the tipping buckets investigated underestimate the rain intensity in the whole measuring range. Several rain gauges have a positive relative deviation, not exceeding 22%, in the low intensity range up to 0.5 mm/min. Positive deviation can be explained by retention of water in the buckets between tips. The reason for the negative deviation is the loss of water during the tips. It leads to the underestimate of the actual intensity. The largest relative deviation in the range of underestimate exceeds 30%. In the range of extreme intensities, the larger buckets (5 cm3) show a lower relative deviation than the smaller (2 cm3) buckets. The gauge characteristic can change in favourable or unfavourable directions after several years. Therefore, the calibration of tipping buckets is recommended at least every 2 to 3 years. [Copyright &y& Elsevier]