Weather Radar and Hydrology Edited by

Key words Multi-Sensor QPE System

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 169-175.

Quantitative precipitation estimate by complementary application of X-band polarimetric radar and C-band conventional radar
ATSUSHI KATO, MASAYUKI MAKI, KOYURU IWANAMI, RYOUHEI MISUMI & TAKESHI MAESAKA

National Research Institute for Earth Science and Disaster Prevention, 3-1, Tennodai, Tsukuba, Ibaraki 305-0006, Japan

[e-mail]
Abstract In recent years, frequent flood damage and fatalities have occurred due to rising levels in urban rivers. Such floods are characterized by their very local nature and rapid development. To provide warnings about such floods, highly accurate Quantitative Precipitation Estimates (QPEs) at a high resolution and in real-time are required. Most QPE research involves the combination of data from raingauges and conventional radar. However, there are insufficient real-time data. The X-band polarimetric radar is useful for real-time QPE with high resolution. Compared with long wavelengths, X-band radars have the advantages of finer resolution, smaller-sized antennas, easier mobility (resulting from smaller antennas for the same beam widths), and lower cost. However, X-band radar has a relatively short observation range and is affected by strong signal attenuation during heavy rainfall. This study examines real-time quantitative rainfall estimation by complementary application of X-band polarimetric radar and C-band conventional radar. A comparison with ground raingauge data verifies that the proposed method is in good agreement with gauge data and is more accurate than conventional radar rainfall estimates.

Key words quantitative precipitation estimate; X-band polarimetric radar; urban flood; specific differential phase

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 176-181.

X-band polarimetric quantitative precipitation estimation: the RHYTMME project
Fadela Kabeche, Jordi Figueras i Ventura, Béatrice Fradon & Pierre Tabary

Météo France DSO-CMR, 42 Av. Coriolis, 31057 Toulouse Cedex, France Toulouse, France

[e-mail]
Abstract This paper presents the current status of the radar data processing chain of the RHYTMME project, aimed at providing real-time quantitative precipitation estimations (QPE) at the local agents in order to minimize the economic and social impact of hazardous weather. The RHYTMME radar network will be composed of four X-band polarimetric radars that will feed data into a centralized processor which will process the data of each individual radar and produce a real-time composite QPE map, which will be transferred to the local operators. Currently there are two radars deployed and the X-band polarimetric processing chain is being finalized.

Key words X-band radar; precipitation; mountain; mask

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 182-187.

Evaluation of the performance of polarimetric quantitative precipitation estimators in an operational environment
Jordi Figueras i Ventura, Béatrice Fradon,
Abdel-Amin Boumahmoud & Pierre Tabary

Centre de Météorologie Radar, Direction de Systèmes d’Observation, Météo France, 42 Av. Coriolis,
31057 Toulouse Cedex, France

[e-mail]
Abstract This paper presents the evaluation of several polarimetric Quantitative Precipitation Estimation algorithms (Pol-QPE), candidates for operational implementation in the Météo France polarimetric weather radar network. The performance at C-band and in ideal conditions of three families of QPE algorithms have been studied: (1) algorithms based on simple Z-R relationships with and without attenuation correction using the differential phase _dp, (2) algorithms based on reflectivity (Z_h) and differential reflectivity (Z_dr), and
(3) algorithms based on specific differential phase (K_dp). The results confirm the superiority of polarimetric algorithms as reported repeatedly in literature. In particular, K_dp-based algorithms are shown to perform quite well at moderate and high rain rates. It is for this reason that at this stage Pol-QPE algorithms based on K_dp are preferred for operational use. To this end, a synthetic algorithm based on attenuation-corrected Z_h for low rain rates and K_dp for higher rain rates has been designed and tested successfully.

Key words polarimetry; polarimetric quantitative precipitation estimation

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 188-193.

VPR corrections of cool season radar QPE errors in the mountainous area of northern California
YOUCUN QI^1,2, JIAN ZHANG³, DAVID KINGSMILL⁴ & JINZHONG MIN¹

1 College of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China

[e-mail]

2 CIMMS, University of Oklahoma, Norman, Oklahoma 73072, USA

3 National Severe Storms Laboratory, Norman, Oklahoma 73072, USA

4 CIRES, University of Colorado & NOAA/Earth System Research Laboratory, Boulder, Colorado, USA
Abstract Non-uniformity of the vertical profile of reflectivity (VPR) is one of the major error sources for radar quantitative precipitation estimation (QPE) in the cool season, especially for mountainous areas. The error is due to two factors: one is that the radar beam samples too high above the ground and misses the microphysics at lower levels; the other is that the radar beam broadens with range and thus cannot resolve vertical variations of reflectivity structure. These errors have posed a major challenge for radar QPE in the complex terrain of northern California. The current study used precipitation profiler observations obtained in this mountainous area and developed a new VPR correction methodology for scanning radar QPE. The precipitation profiler data were used to determine slopes of a linear VPR model in the ice, bright band, and rain regions, and the slope parameters are derived for different geographical areas. The parameterized VPR is then used to correct for scanning-radar QPE. The new methodology was tested using a heavy rain case that occurred over the period 30 December 2005 to 1 January 2006 in northern California, and was found to provide significant improvements over the operational radar QPE.

Key words Vertical Profile of Reflectivity; VPR correction; radar QPE

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 194-200

Toward a physically-based identification of vertical profiles of reflectivity from volume scan radar data
PIERRE-EMMANUEL KIRSTETTER¹, HERVE ANDRIEU²,
BRICE BOUDEVILLAIN³ & GUY DELRIEU³

1 Laboratoire Atmosphères, Milieux, Observations Spatiales, 11, boulevard d’Alembert, 78280 Guyancourt, France

[e-mail]

2 Institut Français des Sciences et Technologies des Transports de l'Aménagement et des Réseaux, Department GER,
Route de Bouaye BP 4129–44341, Bouguenais cedex, France

3 Laboratoire d’étude des Transferts en Hydrologie et Environnement, Domaine universitaire BP 53 38041,
Grenoble cedex 09, France
Abstract A method for identifying VPRs from volumetric radar data is presented that takes into account radar sampling. Physically-based constraints are introduced with a simple VPR model so as to provide a physical description of the vertical structure of rainfall over time-varying geographic domains in which the type of precipitation is homogeneous. The model parameters are identified in the framework of an extended Kalman filter, which ensures their temporal consistency. The method is assessed using the dataset from a volume-scanning strategy for radar quantitative precipitation estimation designed in 2002 for the Bollène radar (France). Positive results have been obtained; the physically-based identified VPRs: (i) present physically consistent shapes and characteristics considering beam effects, (ii) show improved robustness in the difficult radar measurement context of the Cévennes-Vivarais region, and (iii) provide consistent physical insight into the rainfield.

Key words rainfall estimation; vertical profile of reflectivity; Kalman filter; France

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 201-206.

Analysis of a scheme to dynamically model the orographic enhancement of precipitation in the UK
SELENA GEORGIOU, NICOLAS GAUSSIAT & HUW LEWIS

The Met Office, UK

[e-mail]
Abstract Gauge data in upland regions of the UK is sparse and often misrepresents intense precipitation events over small catchments. The production of flash flood warnings relies on high resolution input from the radar composite. It is therefore important that radar measurements of rainfall rate are as accurate as possible and account for the effects of orographic enhancements well. Within the Met Office, the Alpert & Shafir (1989) physically-based method of calculating the orographic enhancement of precipitation has recently replaced the previously operational climatology based one described by Hill (1983). The Alpert & Shafir model takes into account wind speed, wind direction, relative humidity, temperature and the topography of the region. The benefits of using a physical model are numerous. The corrections can be defined at much higher spatial resolution, with the possibility of introducing new fields, such as the vertical wind profile, and making further improvements to the physical model. The offline and operational trial results, as well as results from a post implementation analysis show that accuracy of the precipitation estimates is improved when using Alpert & Shafir’s method.

Key words orographic enhancement; precipitation; vertical profile of reflectivity; seeder feeder

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 207-212.

Impact of quality control of 3-D radar reflectivity data on surface precipitation estimation
Katarzyna Ośródka, Jan Szturc & Anna Jurczyk

Institute of Meteorology and Water Management, 40-065 Katowice, ul. Bratków 10, Poland

[e-mail]
Abstract In the paper the impact of quality control of 3-D radar reflectivity data on surface precipitation estimates is investigated. The developed processing chain for raw 3-D weather radar data aims at the data corrections due to non-meteorological echoes (e.g. from external interferences, specks) and disturbances in meteorological echoes (radar beam blockage, attenuation in rain). All the algorithms were worked out for single polarization radars. Precipitation rates were generated from uncorrected and corrected 3-D reflectivity data and compared in order to assess the algorithm efficiency. The investigation was performed on radars included in the Polish weather radar network POLRAD.

Key words radar; precipitation; quality; correction

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 213-218.

Real-time adjustment of radar data for water management systems using a PDF technique: The City RainNet Project
JOHN V. BLACK^1,2, CHRIS G. COLLIER², JOHN D. POWELL¹,
RICHARD G. MASON¹ & ROD J. E. HAWNT¹

1 Hydro-Logic Ltd, Old Grammar School, Church Street, Bromyard HR7 4DP, UK

[e-mail]

2 UK National Centre for Atmospheric Science, School of Earth & Environment, University of Leeds, Leeds LS2 9JT, UK
Abstract A key challenge of the project is to develop and implement a real-time, rainfall radar adjustment software system. This system will provide rainfall data of reliable accuracy, particularly in convective storm situations. The data produced by the system must have high enough accuracy and reliability to enable water companies and others to be confident in using it in the operation of water management systems. This project will deliver a technically-robust prototype of a commercially viable system, capable of delivering these objectives. The project involves three UK water companies (Yorkshire, Northumbrian and Scottish Water) who have, or will install raingauge networks on approximately 1 km  1 km grids. The approach to the radar data adjustment reported in this paper is based upon using a Probability Matching Method (PMM). Each raingauge outstation comprises a weighing principle raingauge, the OttPluvio2, linked to an ISODAQ GPRS data logger manufactured by Hydro-Logic.

Key words radar; raingauge; probability matching; water companies

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 219-224.

Raingauge quality-control algorithms and the potential benefits for radar-based hydrological modelling
Phil J. Howard, Steven J. Cole, Alice J. Robson &
Robert j. Moore

Centre for Ecology & Hydrology, Wallingford, UK

[e-mail]
Abstract Raingauges and weather radar are essential sources of rainfall information for hydrological modelling and forecasting. However, significant errors in raingauge time-series can drastically affect raingauge-only and combined radar-raingauge rainfall estimates. In turn, these errors can have a negative impact on hydrological model calibration, performance and failure diagnosis. This study considers the automated quality-control of 15-min rainfall totals obtained from 981 tipping-bucket raingauges across England and Wales. The Grid-to-Grid distributed hydrological model, now operated by the Flood Forecasting Centre in support of national flood warning, is used with gridded rainfall estimates to assess the utility of the raingauge quality-control procedures. Although a historical dataset is used here for demonstration and assessment purposes, the automated algorithms have been designed for implementation in real-time.

Key words quality control; raingauge errors; hydrological modelling; automated; flood forecasting; radar

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 225-230.

Blending of radar and gauge rainfall measurements: a preliminary analysis of the impact of radar errors
Daniel sempere-torres¹, Marc Berenguer¹ &
carlos a. velasco-forero²

1 Centre de Recerca Aplicada en Hidrometeorologia, Universitat Politècnica de Catalunya. Gran Capità,
2–4 NEXUS-102, E-08034 Barcelona, Spain

[e-mail]

2 Climate and Water Division, Bureau of Meteorology, GPO Box 727 Hobart, Tasmania 7001, Australia
Abstract Several methodologies have been proposed to combine radar and raingauge measurements with the aim of generating improved quantitative precipitation estimates (QPEs). These methods are based on interpolating point raingauge measurements (implicitly assumed to be “the truth”) and benefiting from the structure of the rainfall field as depicted by the radar. The use of a non-parametric approach based on radar measurements has been recently demonstrated, showing the benefits in the interpolation of raingauge measurements under the hypotheses of the Kriging approach. Several experiments have been carried out over a large number of cases and a variety of regions, Kriging with an external drift (i.e. the radar description of the rainfall field) being the approach showing more robust and (overall) better performance. Here, the impact of the discrepancies between two almost-collocated radars on the blended QPE fields was investigated.

Key words QPE; radar-raingauge blending; spatial variability of rainfall; radar errors; radar calibration

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 231-236.

Application of radar-raingauge co-kriging to improve QPE and quality-control of real-time rainfall data
Hon-yin YEUNG¹, Chun MAN², Sai-tick CHAN¹ & Alan SEED³

1 Hong Kong Observatory, 134A Nathan Road, Kowloon, Hong Kong, China

[e-mail]

2 Department of Physics, the Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

3 Centre for Australian Weather and Climate Research, Bureau of Meteorology, GPO Box 1289, Melbourne 3001, Australia
Abstract Quantitative precipitation estimation (QPE) by weather radar often serves as an important input to hydrological and weather warning operations. Raingauge data are used by operational QPE systems for real-time bias adjustments and as ground truth in the verification of the rainfall estimates and forecasts. Raingauges are also subject to malfunction and quality-control is required before the data can be used quantitatively. A recently proposed procedure based on an analysis of differences between the radar rainfall estimate and the gauge observation and an interpolation of the local raingauges to the gauge site has been enhanced and is described in this paper.

Key words precipitation estimation; co-kriging; raingauge; quality control; Hong Kong

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 237-242.

Combination of radar and raingauge observations using a
co-kriging method
Chung-yi Lin¹ & tim hau lee²

1 Taiwan Typhoon and Flood Research Institute, 12F, No. 97, Sec. 1, Roosevelt Rd., Taipei 10093, Taiwan

[e-mail]

2 National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan
Abstract A rainfall estimation algorithm using a co-kriging method which combines radar and raingauge measurements is presented in this study. In the first part, error-free raingauge data and four different known error-structured radar observations are used to examine the abilities of two ordinary co-kriging techniques and two universal co-kriging techniques to correctly estimate spatial distribution of rainfall. The four radar observation errors are: (1) additive white noise error (WN); (2) additive correlative error with bias (AE); (3) multiplicative correlative error (ME); and (4) trend error varying with radar range (TE). In the second part, one case study of true typhoon data is used to verify the capability of this method to utilize real data. The ordinary co-kriging (OCK) technique utilises the linear combination of all raingauge observations and the radar observation collocated with estimated grid. The modified ordinary co-kriging (MOCK) technique utilizes the radar observations on top of all raingauges in addition to the data used by OCK technique. The minimum error variance estimation of universal co-kriging (UCK) utilizes the gauge data only to form the covariance matrix. Based on the collocated true rainfalls and radar observations, and following a linear model assumption, the unbiased conditions are derived. UCKT is a UCK technique that includes satisfying the spatial trend unbiased condition. Case study results illustrate that OCK is the only technique that cannot avoid AE error from going into rainfall rate estimates. Both MOCK and UCKT can effectively prevent AE and TE error from entering the estimates, and reduce the influence of ME error. According to the statistics of the case studies, MOCK had the lowest root mean square error. The major advantage of UCK and UCKT is that it is not necessary to provide the semi-variograms involving radar data.

Key words co-kriging; ordinary Kriging; universal Kriging; rain-rate estimate; radar observation; gauge observation;
data fusion; spatial interpolation; observing system experiment

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 243-248.

Comparison of different radar-gauge merging techniques in the NWS multi-sensor precipitation estimator algorithm
Emad habib¹, Lingling Qin¹ & Dong-Jun Seo²

1 Department of Civil Engineering, University of Louisiana at Lafayette, PO Box 42991, Lafayette, Louisiana 70504, USA

[e-mail]

2 Department of Civil Engineering, The University of Texas at Arlington, Box 19308, Rm 438 Nedderman Hall,
416 Yates St, Arlington, Texas 76019-0308, USA
Abstract This study performed an inter-comparison analysis of multi-level products of the radar-based multi-sensor precipitation estimation (MPE) algorithm. The main objective was to provide the user community and algorithm developers with insights on the potential value of increasing degrees of complexities in the algorithm in terms of bias removal and optimal merging with gauge observations. Different MPE products were considered: a gauge-only product, a radar-only product, a mean-field bias adjusted product, a local bias-adjusted product, and two products that are based on merging bias-adjusted products with gauge observations. The evaluation was conducted at the MPE native resolution (4×4 km² and hourly) using independent surface rainfall observations from a dense raingauge network in Louisiana, USA. The results demonstrate that some best-intended schemes for extensive radar and raingauge data processing do not lead to clear improvements and can even degrade the final products in some respects.

Key words rainfall; radar; multi-sensor; product; evaluation

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012)., 294-254

Long-term evaluation of radar QPE using VPR correction and radar-gauge merging
EDOUARD GoUDENHOOFDT & LAURENT DELOBBE

Royal Meteorological Institute of Belgium, Avenue Circulaire 3 B-1180 Brussels, Belgium

[e-mail]
Abstract A new operational QPE algorithm based on C-band radar measurements has been developed. It is based on the computation of a mean apparent VPR. 24-h radar rainfall accumulations are combined with dense raingauge measurements using methods of various complexity. An independent raingauge network is used for verification. The relative performance of the methods is assessed using several statistics. A case analysis shows that the VPR QPE corrects for the high reflectivity circles seen on PCAPPI images. However, 2004–2010 statistics show that its benefit remains limited, especially after the application of merging methods. A seasonal analysis shows that the benefit of the radar is high in summer, while the VPR estimates have a slight positive or negative effect depending on the month and the method. The relative performance of the VPR estimates decreases with radar distance. These mitigated results suggest that a deeper analysis is needed to improve the method.

Key words C-band radar; VPR; QPE; merging; verification; Belgium

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 255-260

A 10-year (1997–2006) reanalysis of Quantitative Precipitation Estimation over France: methodology and first results
Pierre Tabary¹, Pascale Dupuy¹, Guy L’Henaff¹,
CLAUDINE GUEGUEN¹, LAETITIA MOULIN¹, Olivier Laurantin², Christophe Merlier² & Jean-Michel Soubeyroux³

1 Centre de Météorologie Radar, DSO, Météo France, Toulouse, France

[e-mail]

2 Division Coordination Etudes et Prospective, DSO, Météo France, Toulouse

3 Direction de la Climatologie, Météo France, Toulouse, France
Abstract In order to provide a common reference for hydrologists (e.g. for calibrating model parameters, assessing the added value of inputting high space-time resolution data in hydrological models), Météo France is currently running a national collaborative project aimed at producing a high-resolution (1 km²),
10-year reference database (1997–2006) of hourly Quantitative Precipitation Estimations (QPE) covering the entire French metropolitan territory with no spatial nor temporal gaps. The input data that are used are the individual 5 min 512  512 km² pseudo-CAPPI radar reflectivity images of the French radar network and quality-controlled hourly and daily (from 6 UTC to 6 UTC) raingauges. Several validation exercises have been performed to validate the various steps of the processing chain. In particular, the final product – 1 km² composite hourly accumulation maps – has been evaluated with independent raingauge data over one year in two different geographical / meteorological contexts.

Key words radar Quantitative Precipitation Estimation; kriging; radar–raingauge merging

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012) 261-266.

Temporal and spatial variability of rainfall at urban hydrological scales
I. EMMANUEL¹, E. LEBLOIS², H. ANDRIEU³ & B. FLAHAUT¹

1PRES L’UNAM, Ifsttar, Département GER, CS4, 44341 Bouguenais, France

[e-mail]

2 CEMAGREF, 3 B Quai Chauveau, 69009 Lyon, France

3 PRES L’UNAM, Ifsttar, Département GER and IRSTV FR CNRS 2488 Bouguenais, France
Abstract The main objective of this paper is to characterize the spatial and temporal variability of rainfall at scales that are consistent with urban hydrological applications. In this way, a total of 24 rain periods have been analysed according to a geostatistical approach. This analysis has focused on the non-zero rainfall variogram. The studied rain periods were recorded by the weather radar of Treillières (10 km north of Nantes, France) in 2009. This radar device provides rainfall radar images with a high level of spatial resolution (250  250 m²) and instantaneous temporal resolution. Results indicated four different types of rainfall fields, which display very different variability scales, including double structures within the same field. This study highlights the benefit of radar images featuring high temporal and spatial resolution, which in turn allow studying small-scale variability.

Key words rainfall structure; geostatistics; hydrological scales

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 269-274.

Comparison of optical flow algorithms for precipitation field advection estimation
Thomas Pfaff & András Bárdossy

Hydrology and Geohydrology, Institute of Hydraulic Engineering, University of Stuttgart, Germany

[e-mail]
Abstract Estimates of the advection field as derived from successive weather radar images are not only an essential piece of information for precipitation nowcasting, they can also be of value in order to improve the quality of radar-based precipitation estimates themselves. In order to develop a correction scheme for radar accumulations using advection information, three different methods to determine the optical flow between two radar images were tested. The main criteria for algorithm selection were: (a) execution speed to allow application in an operational setting, (b) the quality of the estimated advection field, assessed by visual inspection and common error measures like RMSE and MAE, and (c) the robustness of the algorithm, i.e. the dependence of the estimation quality on the choice of their governing parameters. A simple block matching algorithm, an optical flow algorithm based on image intensity gradients and an approach that uses information on multiple image scales to optimize the search pattern of an extended block matching method were considered. All three methods were reasonably fast for calculating the advection fields and showed a similar distribution of their error measures. The last algorithm showed the most robust behaviour, the estimated advection field being virtually independent of the parameter choice. Applying the accumulation correction scheme using advection fields calculated by this last algorithm, improved the agreement between radar estimates and station measurements for the majority of the stations.

Key words weather radar; advection; optical flow

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 275-280.

Extending a Lagrangian extrapolation forecast technique to account for the evolution of rainfall patterns over complex terrain
Pradeep V. Mandapaka, Urs Germann, Luca Panziera & Alessandro Hering

146 via ai Monti, Locarno Monti, Switzerland

[e-mail]
Abstract In this study, we employed a Lagrangian extrapolation scheme (MAPLE) to obtain short-term (lead times <5 h) rainfall forecasts over a large region broadly centred on Switzerland. The high-resolution forecasts from MAPLE were then evaluated against the radar observations for 20 summer rainfall events using categorical and continuous verification techniques. The verification results were then compared with Eulerian extrapolation forecasts. In general, Lagrangian persistence forecasts outperformed Eulerian persistence forecasts. Although MAPLE performed well for short lead times, the performance deteriorated rapidly with increase in lead time. Results also showed that the predictability of the MAPLE model depends on the spatial correlation structure and temporal evolution of the rainfall events.

Key words radar-rainfall; predictability; lifetime; MAPLE

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 281-286.

Nowcasting of orographic rainfall by using Doppler weather radar
L. PANZIERA, U. GERMANN, A. HERING & P. MANDAPAKA

MeteoSvizzera, via ai Monti 146, CH-6605 Locarno Monti, Switzerland

[e-mail]
Abstract A novel radar-based heuristic tool for nowcasting orographic precipitation is presented. The system benefits from the strong relation, due to the orographic forcing, between mesoscale flows, air-mass stability and rainfall patterns. The system is based on an analogue approach: past situations with mesoscale flows, air mass stability and rainfall patterns most similar to those observed at the current instant are identified by searching in a large historical data set. Deterministic and probabilistic forecasts are then generated every five minutes as new observations are available, based on the rainfall observed by radar after the analogous situations. This approach constitutes a natural way to incorporate evolution of precipitation into the nowcasting system and to express forecast uncertainty by means of ensembles. A total of 127 days of long-lasting orographic precipitation constitutes the historical archive in which the analogous situations are searched. The system is originally developed for the Lago Maggiore region in the southern part of the European Alps, but it can be extended to other mountainous regions given the availability of radar data and the presence of a strong orographic forcing. An evaluation of the skill of the system shows that the heuristic tool performs better than both Eulerian persistence and the COSMO2 numerical model.

Key words Alpine radar; nowcasting; analogues; orographic precipitation; mesoscale flows; air mass stability; IMPRINTS

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 287-292

The relationships between the upstream wind and orographic heavy rainfall in southwestern Taiwan for typhoon cases
LEI FENG¹, PAO-LIANG CHANG² & BEN JONG-DAO JOU³

1 Taiwan Typhoon and Flood Research Institute, 11F, No. 97, Sec. 1, Roosevelt Road, Taipei 10093, Taiwan

[e-mail]

2 Central Weather Bureau, 64 Gongyuan Road, Taipei 10048, Taiwan

3 Department of Atmospheric Science, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan, APEC Research Center for Typhoon and Society (ACTS)
Abstract Typhoon Morakot (2009) landed on northern Taiwan and then moved toward the northwest. Extreme heavy rainfall occurred in the mountainous region of southwest Taiwan. It was noticed that there were very strong horizontal westerly flows upstream of the mountain in southwest Taiwan. The relation between this upstream horizontal westerly wind and the heavy rain over the mountain is the major focus of this study. The 24-h maximum rainfall produced by Morakot was >1500 mm, and >20 stations in the area measured rainfall >1000 mm in 24 h. An algorithm was proposed to predict the extreme orographic heavy rain over southwestern Taiwan using radar-derived low-level horizontal winds. The Chigu radar is located 80 km upstream (westerly wind) of the mountainous regions. The EVAD technique was applied to retrieve the horizontal winds. The averaged horizontal winds between 0.5 and 3.0 km height are treated as the upstream low-level flow impinging on the mountain. A very good relationship between the low-level averaged speed and the hourly rainfall amount was achieved and the linear correlation coefficient is near 0.88. A similar algorithm was applied to two other typhoons: Haitang and Talim both in 2005; linear correlation coefficients of 0.80 and 0.84 were obtained, respectively. It is suggested that the upstream velocity of the flow determined the amount of heavy rainfall over the mountainous region in the strong wind regimes.

Key words typhoon; orographic heavy rain; Doppler radar; horizontal wind speed upstream of the mountain

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 293-298

Use of ensemble radar estimates of precipitation rate within a stochastic, quantitative precipitation nowcasting algorithm
Clive Pierce¹, Katie Norman¹ & Alan Seed²

1 Met Office, FitzRoy Road, Exeter EX1 3PB, UK

[e-mail]

2 Australian Bureau of Meteorology, The Centre for Australian Weather and Climate Research, GPO Box 1289, Melbourne, Victoria 3001, Australia
Abstract Several techniques for the generation of ensembles of radar observations are described and evaluated. These have been combined to generate ensemble estimates of surface precipitation rate for use in conjunction with the Short Term Ensemble Prediction System. STEPS is an operational, quantitative precipitation nowcasting algorithm developed jointly by the Met Office and the Australian Bureau of Meteorology. It generates ensemble nowcasts of precipitation rate and accumulation by scale-selectively blending a weather radar-based, extrapolated analysis of surface precipitation rate with a recent precipitation forecast from a high-resolution configuration of the Unified Model, and a time series of synthetically generated precipitation fields (noise) with space–time statistical properties inferred from radar. Currently, STEPS incorporates an observation uncertainty algorithm based upon on analysis of Z-R errors. In this paper, the performance of STEPS precipitation nowcast ensembles, generated using radar ensembles, is compared with that of operational STEPS precipitation nowcasts, produced using unperturbed observations.

Key words radar; observation error; nowcast; ensembles

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 299-304.

Probabilistic forecasting of rainfall from radar nowcasting and hybrid systems
SARA LIGUORI & MIGUEL RICO-RAMIREZ

University of Bristol, Department of Civil Engineering, Bristol BS8 1TR, UK

[e-mail]
Abstract The use of Quantitative Precipitation Forecasts (QPFs) from either Numerical Weather Prediction (NWP) or radar nowcasting models in flood forecasting systems extends the time available to issue warnings and take actions. However, uncertainty in the rainfall input affects the accuracy of flow predictions. Radar nowcasts have a higher skill at short lead times, whereas NWP models produce more accurate forecasts at longer lead times. Hybrid systems, merging NWP and radar-based forecasts, have been developed to produce more skilful forecasts than either independent component (i.e. NWP/radar nowcasting). This study aims at assessing radar nowcasts and hybrid forecasts provided by the state-of-the-art model STEPS. The forecasts were run on a 1000 km  1000 km domain covering the UK, at 2-km spatial and 15-min temporal resolutions. Results show that the forecasting system benefits from the blending with the NWP forecasts.

Key words QPFs; ensemble forecasting; STEPS; nowcasting; hybrid forecasts

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 305-310.

PhaSt: stochastic phase-diffusion model for ensemble rainfall nowcasting
N. ReBORA & F. SILVESTRO

CIMA Research Foundation, Via Magliotto 2, 17100 Savona, Italy

[e-mail]
Abstract Hydrometeorological hazard management often requires the development of reliable statistical rainfall nowcasting systems. Ideally, such procedures should be capable of generating stochastic ensemble forecasts of precipitation intensities on scales of the order of a few kilometres, up to a few hours in advance. Ensemble rainfall nowcasting allows for characterizing the uncertainty associated with nowcasting procedures by providing a probabilistic forecast of the future evolution of an event. Here we discuss an ensemble rainfall nowcasting technique, named PhaSt (Phase Stochastic), based on the extrapolation of radar observations by a diffusive process in Fourier space. The procedure generates stochastic ensembles of precipitation intensity forecast fields where individual ensemble members can be considered as different possible realizations of the same precipitation event. The model is tested on a data set of rainfall events measured by the C-POL radar of Mt Settepani (Liguria, Italy) and its performance verified in terms of standard probabilistic scores.

Key words nowcasting; ensemble; probabilistic forecast; rainfall

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 311-316.

Ensemble radar nowcasts – a multi-method approach
Alrun Tessendorf & Thomas Einfalt

Hydro & Meteo GmbH & Co. KG, Breite Straße 6-8, D-23552 Lübeck, Germany

[e-mail]
Abstract Radar nowcasting has for a long time been a competition between individual approaches with their strengths and weaknesses. The introduction of ensembles makes it possible to benefit from several techniques and can help in forecast applications by providing statistical information. This study focuses on how to prepare results of ensemble forecasts for risk assessment in real-time warning applications. A set of ensembles, combining runs from four forecast methods with perturbed initial conditions, is constructed and the results are evaluated using six different criteria. For predicting the current forecast quality from the ensemble spreading, quality parameters based on the contingency table were derived from the ensemble forecasts.

Key words rainfall forecast; radar; ensembles; nowcasting; risk assessment; forecast quality

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012)., 317-322

Application of Error-Ensemble prediction method to a short-term rainfall prediction model considering orographic rainfall
Eiichi Nakakita¹, Tomohiro Yoshikai² & SUNmin kim²

1 Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji 611-0011, Kyoto, Japan

[e-mail]

2 Graduate School of Engineering, Kyoto University, Kyoto-Daigaku-Katsura 615-8510, Kyoto, Japan
Abstract In order to improve the accuracy of short-term rainfall predictions, especially for orographic rainfall in mountainous regions, a conceptual approach and a stochastic approach were introduced into a radar image extrapolation using a Translation Model. In the conceptual approach, radar rainfall measurements are separated into orographic and non-orographic rain fields by solving physically-based equations, including additional atmospheric variables, such as vertical wind velocity. In the stochastic approach, mean bias of current prediction errors was estimated and used to adjust mean prediction bias. Furthermore, the vertical wind velocity was updated with the mean bias for convective rainfall. As a result, 1-h prediction accuracy in mountainous regions was much improved for the case study. In the future, improved updating procedures can be expected to allow more accurate predictions.

Key words short-term rainfall prediction; orographic rainfall; ensemble forecasting prediction; prediction error

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 323-329.

On the DWD quantitative precipitation analysis and nowcasting system for real-time application in German flood risk management
TANJA WINTERRATH¹, Wolfgang Rosenow² & elmar weigl¹

1 Deutscher Wetterdienst, Department of Hydrometeorology, Frankfurter Straße 135, 63067 Offenbach, Germany

[e-mail]

2 Deutscher Wetterdienst, Department of Research and Development, Michendorfer Chaussee 23, 14473 Potsdam, Germany
Abstract Quantitative precipitation analyses and forecasts with high temporal and spatial resolution are essential for hydrological applications in the context of flood risk management. Therefore, the Deutscher Wetterdienst, together with representatives of the water management authorities of the German federal states have developed high-resolution quantitative precipitation analysis and nowcast products based on the combination of surface precipitation observations and weather radar-based precipitation estimates. Gauge adjustment is performed hourly, making use of 16 operational radar systems and approximately 1300 conventional precipitation measurement devices. The nowcast algorithm is based on the advection of precipitation elements based on the mapping of precipitation patterns in successive image data. The subsequent quantification makes use of the latest adjustment process. Additional information about the precipitation phase, required for the determination of the discharge efficiency of precipitation, is retrieved by combining various observational and model data with the radar-based forecasts. The nowcasting system is supplemented by a qualitative hail forecast.

Key words radar; precipitation; gauge adjustment; nowcasting; quantification; precipitation phase; real time;
risk management; DWD; Germany

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 330-335.

Aspects of applying weather radar-based nowcasts of rainfall for highways in Denmark
M. R. Rasmussen¹, S. Thorndahl¹ & M. Quist²

1 Aalborg University, Department of Civil Engineering, Sohngaardsholmsvej 57, DK-9000 Aalborg, Denmark

[e-mail]

2 Danish Road Directorate, Thomas Helstedsvej 22, DK-8660 Skanderborg, Denmark
Abstract This work investigates three different approaches to nowcasting rainfall for highways. The simplest method is based on using the observed precipitation field at the beginning of the trip. The most developed nowcast is based on a COTREC nowcaster, which is dynamically adjusted to online raingauges. The nowcasts are performed with a lead time of up to 2 h. The average speed on Danish highways varies between 110 and 130 km/h. As a result, the performance of the nowcast is dependent on the direction of the precipitation and the direction and speed of the road users, as well as the type of precipitation.

Key words nowcast; highway; traffic conditions; weather radar

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 336-341.

Use of radar data in NWP-based nowcasting in the Met Office
SUSAN BALLARD¹, ZHIHONG LI¹, DAVID SIMONIN¹, HELEN BUTTERY¹, CRISTINA CHARLTON-PEREZ¹, NICOLAS GAUSSIAT² &
LEE HAWKNESS-SMITH¹

1 Met Office, Dept of Meteorology, University of Reading, Reading RG6 6BB, UK

[e-mail]

2 Met Office, FitzRoy Road, Exeter EX31 3PB, UK
Abstract The Met Office is developing an hourly cycling 1.5 km resolution NWP-based nowcast system
(0–6 h), principally for prediction of convective storms for flood forecasting. Test suites were run on a domain covering southern England and Wales nested in a UK 4 km domain. These have used 3D-Var or 4D-Var in combination with latent heat nudging of radar-derived precipitation rates and humidity nudging based on 3D cloud cover analyses. An example shows the precipitation forecast compared to the current extrapolation nowcast system. The results of a trial, showing positive impact of Doppler radar winds out to about 5 h on forecasts of precipitation from the 3D-Var system, are presented. The paper also discusses work underway to allow assimilation of rain-rates and radar reflectivity within the variational schemes and the potential to measure the low-level humidity impact on radar refractivity as an additional source of data to improve flood forecasting.

Key words NWP; variational data assimilation; radar; flood forecasting; UK; nowcasting; Doppler winds; reflectivity

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 342-347.

Quality monitoring of UK network radars using synthesised observations from the Met Office Unified Model
SELENA GEORGIOU¹, NICOLAS GAUSSIAT¹, DAWN HARRISON¹ &
SUE BALLARD²

1 The Met Office, Exeter, UK

[e-mail]

2 Advanced Nowcasting Research Group, Met Office, Department of Meteorology, Univ. Reading, Reading RG6 6BB, UK
Abstract The Met Office radar processing system delivers quality-controlled radar reflectivities to NWP. Quality information and radar reflectivity data are then passed to the Observation Processing System (OPS) where synthetic observations are calculated using model fields interpolated at the exact observation locations. Long-term statistical comparison between synthetic and real observations has the advantage of identifying individual radar calibration problems through relative comparisons with other radars. The effectiveness of the forward modelling of the reflectivity can also be evaluated through absolute statistical comparisons. Presented here is an analysis of statistical information derived from the quality monitoring system. Included is a description of the contribution made to the radar signal bias with range as a result of the combined effects of the bright band, attenuation by rain and clouds and beam broadening. The results are used to demonstrate that the atmospheric gaseous attenuation makes a significant contribution to the overall range bias, and it is therefore beneficial to account for this within the radar site processing.

Keywords quality control; unified model; data assimilation; model verification; gaseous attenuation

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 348-353.

Operational radar refractivity retrieval for numerical weather prediction
J. C. NICOL¹, K. bartholemew¹, T. DARLINGTON², A. J. Illingworth¹
& M. KItchen²

1 University of Reading, Reading, UK

[e-mail]

2 UK Met Office, Exeter, UK
Abstract This work describes the application of radar refractivity retrieval to the C-band radars of the UK operational weather radar network. Radar refractivity retrieval allows humidity changes near the surface to be inferred from the phase of stationary ground clutter targets. Previously, this technique had only been demonstrated for radars with klystron transmitters, for which the frequency of the transmitted signal is essentially constant. Radars of the UK operational network use magnetron transmitters which are prone to drift in frequency. The original technique has been modified to take these frequency changes into account and reliable retrievals of hourly refractivity changes have been achieved. Good correspondence has been found with surface observations of refractivity. Comparison with output of the Met Office Unified Model (UM) at 4-km resolution indicate closer agreement between the surface observations and radar-derived refractivity changes than those represented in the UM. These findings suggest that the assimilation of radar-derived refractivity changes in Numerical Weather Prediction models could help improve the representation of near-surface humidity.

Key words radar refractivity; humidity; NWP

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 354-359.

Assessment of radar data assimilation in numerical rainfall forecasting on a catchment scale
jia liu¹, mIchaela bray^1,2 & dawei han¹

1 Water and Environmental Management Research Centre, Department of Civil Engineering, University of Bristol,
Bristol BS8 1TR, UK

[e-mail]

2 Institute of Environment and Sustainability, School of Engineering, Cardiff University, Cardiff CF24 0DE, UK
Abstract Numerical Weather Prediction (NWP) model is gaining popularity among the hydrometeorological community for rainfall forecasting. However, data assimilation of the NWP model with real-time observations, especially the weather radar data, is still a challenging problem. The NWP model has its advantage in modelling the physical processes of storm events, while its accuracy is negatively influenced by the “spin-up” effect and the errors in the model driving. To fully utilise the available information and to improve the performance of the NWP model, observations need to be assimilated in real-time. This study focuses on a small catchment located in southwest England with a drainage area of 135.2 km². The Weather Research and Forecasting (WRF) model and the three-dimensional variational (3DVar) data assimilation system are applied for the assimilation of radar reflectivity together with surface and upper-air observations. Four 24-h storm events are selected, with variations of rainfall distribution in time and space. The improvement in rainfall forecasts caused by data assimilation is examined for four types of events. For a better assimilation, a radar correction ratio is further developed and applied to the radar data.

Key words numerical rainfall forecasting; WRF; 3DVar data assimilation; radar reflectivity; radar bias correction

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 360-366.

Convective cell identification using multi-source data
ANNA JURCZYK, JAN SZTURC & KATARZYNA OŚRÓDKA

Institute of Meteorology and Water Management, 40-065 Katowice, ul. Bratków 10, Poland

[e-mail]
Abstract Identification of convective cells is an important issue for detecting severe meteorological phenomena and precipitation nowcasting. The proposed model that classifies each individual radar pixel as convective or stratiform was developed based on multi-source data and applying a fuzzy logic approach. For both classes (stratiform or convective), membership functions for all investigated parameters were defined and aggregated as weighted sums. Comparison of the weighted sums decides which category a considered radar pixel belongs to. Each membership function was determined for selected parameters from: weather radar network, satellite Meteosat 8, lightning detection system, and numerical weather prediction (NWP) model. Then convective pixels were clustered to obtain individual cells, assuming that cells with a small distance between their maxima are joined.

Key words precipitation; convection

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 369-374.

Guy delrieu¹, laurent bonnifait¹,
pierre-emmanuel kirstetter^1,2 & brice boudevillain¹

1 Laboratoire d’étude des Transferts en Hydrologie et Environnement, Grenoble, France

[e-mail]

2 National Severe Storms Laboratory, Norman, Oklahoma, USA
Abstract Characterizing the error structure of radar quantitative precipitation estimation (QPE) is recognized as a major issue for applications of radar technology in hydrological modelling. This topic is further investigated in the context of the Cevennes-Vivarais Mediterranean Hydrometeorological Observatory dedicated to improving observation and modelling of extreme hydrometeorological events in the Mediterranean. The reference rainfall problem is firstly addressed: after quality-control of the raingauge measurements, various interpolation techniques (isotropic and anisotropic Ordinary Kriging, Universal Kriging with external drift) are implemented and compared through a cross-validation procedure. Then, the block Kriging technique allows the estimation and selection of reference values for a series of time-steps
(1–12 h) and hydrological mesh sizes (5–50 km²). The conditional distributions of the residuals between radar and reference values are modelled using generalized additive models for location scale and shape. The distributions are analysed for the operational real-time radar products and the Observatory re-analysed products, the latter being by construction less affected by conditional bias. As expected, the error model is dependent on the space and time scales considered. The hourly raingauge network is found to be not dense enough for providing reliable spatial estimations for sub-daily time-steps.

Key words Mediterranean heavy precipitation; weather radar; quantitative precipitation estimation; error model;
space and time scales

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 375-381.

Investigating radar relative calibration biases based on four-dimensional reflectivity comparison
bong-chul seo¹, witold F. krajewski¹ & james A. smith²

1 IIHR-Hydroscience & Engineering, The University of Iowa, Iowa City, Iowa 52242, USA

[e-mail]

2 Department of Civil and Environmental Engineering, Princeton University, Princeton, New Jersey 08544, USA
Abstract A methodology to compare radar reflectivity data observed from two different ground-based radars is proposed. This methodology is motivated primarily by the need to explain relative differences in radar-rainfall products and to establish sound merging procedures of multi-radar observing networks. The authors compare radar reflectivity for well-matched radar sampling volumes viewing common meteorological targets. While spatial and temporal interpolation is not performed in order to prevent any distortion arising from the averaging scheme, the authors considered temporal separation and three-dimensional matching of two different sampling volumes based on the original polar coordinates of radar observation. Since the proposed method assumes radar beam propagation under the standard atmospheric condition, we do not consider anomalous propagation cases. The reflectivity comparison results show some systematic differences year to year, but the variability of those differences is fairly large due to the sensitive nature of radar reflectivity measurement. The authors performed statistical tests to check reflectivity difference consistency for consecutive periods.

Key words radar reflectivity; radar-rainfall; radar calibration bias

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 382-387.

A quality evaluation criterion for radar rain-rate data
Chulsang Yoo, Jungsoo Yoon, Jungho Kim, Cheolsoon Park &
CHANGHYUN JUN

School of Civil, Environmental and Architectural Engineering, College of Engineering, Korea University,

Seoul 136-713, Korea

[e-mail]
Abstract This study proposed a radar rain-rate quality criterion (RRQC), a measure of goodness for the radar rain-rate. The RRQC proposed is based on the similar concept of total variance in the statistical analysis of variance, which considers both the bias and variability of radar rain-rate with respect to the raingauge rain-rate. The RRQC was estimated for three storm events with the raw radar data, along with improved versions based on G/R correction and merging by co-Kriging. Additionally, these radar data were applied to the runoff analysis of the Choongju Dam Basin, Korea. By investigating the relation between the RRQC in the rain-rate input and the errors in the runoff output, a minimum quality of radar rain-rate applicable to the rainfall–runoff analysis was explored.

Key words radar rain-rate; RRQC; G/R ratio; co-Kriging; rainfall–runoff analysis

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 388-393.

Radar Quality Index (RQI) – a combined measure for beam blockage and VPR effects in a national network
Jian ZHANG¹, YOUCUN QI^2,3, Carrie LANGSTON² & BRIAN KANEY²

1 National Severe Storms Lab, 120 David L Boren Blvd., Norman, Oklahoma 73072, USA

[e-mail]

2 Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, 120 David L Boren Blvd, Norman, Oklahoma 73072, USA

3 Nanjing University of Information Science and Technology, Nanjing, China
Abstract The next-generation multi-sensor quantitative precipitation estimation (QPE), or “Q2”, is an experimental hydrometeorological system that integrates data from radar, raingauge, and atmospheric models and generates high-resolution precipitation products on a national scale in real-time. The quality of the Q2 radar QPE varies in space and in time due to a number of factors, which include: (1) errors in measuring radar reflectivity; (2) segregation of precipitation and non-precipitation echoes; (3) uncertainties in Z–R relationships; and (4) variability in the vertical profile of reflectivity (VPR). In the current study, a Radar QPE Quality Index (RQI) field is developed to present the radar QPE uncertainty associated with VPRs. The RQI field accounts for radar beam sampling characteristics (blockage, beam height and width) and their relationships with respect to the freezing level. A national RQI map is generated by mosaicking single radar RQI fields. The radar quality information is useful to hydrological users and can add value in radar rainfall applications.

Key words radar QPE quality; beam blockage; VPR; national radar network

Weather Radar and Hydrology

(Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 351, 2012), 394-399.

1.