Science.gov

Sample records for weather radar rainfall

  1. A study on weather radar data assimilation for numerical rainfall prediction

    NASA Astrophysics Data System (ADS)

    Liu, J.; Bray, M.; Han, D.

    2012-09-01

    Mesoscale NWP model is gaining more attention in providing high-resolution rainfall forecasts at the catchment scale for real-time flood forecasting. The model accuracy is however negatively affected by the "spin-up" effect and errors in the initial and lateral boundary conditions. Synoptic studies in the meteorological area have shown that the assimilation of operational observations especially the weather radar data can improve the reliability of the rainfall forecasts from the NWP models. This study aims at investigating the potential of radar data assimilation in improving the NWP rainfall forecasts that have direct benefits for hydrological applications. The Weather Research and Forecasting (WRF) model is adopted to generate 10 km rainfall forecasts for a 24 h storm event in the Brue catchment (135.2 km2) located in Southwest England. Radar reflectivity from the lowest scan elevation of a C-band weather radar is assimilated by using the three dimensional variational (3D-Var) data assimilation technique. Considering the unsatisfactory quality of radar data compared to the rain gauges, the radar data is assimilated in both the original form and an improved form based on a real-time correction ratio developed according to the rain gauge observations. Traditional meteorological observations including the surface and upper-air measurements of pressure, temperature, humidity and wind speed are also assimilated as a bench mark to better evaluate and test the potential of radar data assimilation. Four modes of data assimilation are thus carried out on different types or combinations of observations: (1) traditional meteorological data; (2) radar reflectivity; (3) corrected radar reflectivity; (4) a combination of the original reflectivity and meteorological data; and (5) a combination of the corrected reflectivity and meteorological data. The WRF rainfall forecasts before and after different modes of data assimilation is evaluated by examining the rainfall cumulative

  2. Estimation of Design Rainfall from Weather Radar Data - a Case Study for the Hannover Area

    NASA Astrophysics Data System (ADS)

    Haberlandt, U.; Berndt, C.

    2015-12-01

    The estimation of design rainfall requires long-term precipitation observations in high temporal resolution. Those data are available only with poor spatial density, which usually entails regionalization for their practical application. An alternative would be to utilize the high spatial resolution of weather radar for the estimation of design rainfall. Meanwhile the observation length of many operational radar instruments extend over a time period of 10 years, which suggests to analyze their benefits for estimating design rainfall. In this study, 13 years of observations from the Hannover radar station located in Northern Germany are analyzed together with about 50 recording rain gauges in the observation range of the regarding their reproduction of extreme rainfall statistics. Pure radar data and radar-station merging products are analyzed for rainfall durations from 5 minutes to 6 hours and return periods from 1 year to 30 years. Partial duration series of the extremes were derived from the data and probability distributions fitted. The performance of the design rainfall estimates is assessed based on cross validations for observed station points, which are used as reference. For design rainfall estimation using the pure radar data, the pixel value at station location is taken; for the merging products, spatial interpolation methods are applied. The results show, that pure radar data are not suitable for the estimation of extremes. They usually lead to an overestimation compared to the observations, which is opposite to the usual behavior of radar rainfall for average intensities. However, some of the merging products between radar and station data can provide a better estimate for extremes as the station data alone, especially for the longer durations. Main condition for a good performance is that the radar data are adjusted to daily observed rainfall sums prior to their application.

  3. Recalibration of cumulative rainfall estimates by weather radar over a large area

    NASA Astrophysics Data System (ADS)

    Mazza, Alessandro; Antonini, Andrea; Melani, Samantha; Ortolani, Alberto

    2015-01-01

    The real-time measurement of rainfall is a primary information source for many purposes, such as weather forecasting, flood risk assessment, and landslide prediction and prevention. In this perspective, remote sensing techniques to monitor rainfall fields by means of radar measurements are very useful. In this work, a technique is proposed for the estimation of cumulative rainfall fields averaged over a large area, applied on the Tuscany region using the Italian weather radar network. In order to assess the accuracy of radar-based rainfall estimates, they are compared with coincident spatial rain gauge measurements. Observations are compared with average rainfall over areas as large as a few tens of kilometers. An ordinary block kriging method is applied for rain gauge data spatialization. The comparison between the two types of estimates is used for recalibrating the radar measurements. As a main result, this paper proposes a recalibrated relationship for retrieving precipitation from radar data. The accuracy of the estimate increases when considering larger areas: an area of 900 km2 has a standard deviation of less than few millimeters. This is of interest in particular for extending recalibrated radar relationships over areas where rain gauges are not available. Many applications could benefit from it, from nowcasting for civil protection activities, to hydrogeological risk mitigation or agriculture.

  4. Rainfall resolution from weather radars and their application in urban drainage modelling

    NASA Astrophysics Data System (ADS)

    Bruni, G.; ten Veldhuis, J. A. E.; Otto, T.; Leijnse, H.

    2012-04-01

    Urban hydrological modelling requires high resolution rainfall data to be able to simulate fast runoff processes and related short response times. Over the last three decades, rainfall input into urban hydrological and hydrodynamic models has often been restricted to a single rain gauge in or near the catchment, rendering rainfall input one of the main sources of uncertainty in model calculations. In recent years, rainfall data from weather radars that provide space-time estimates of rainfall are becoming increasingly available. C-band and S-band radars have been used for operational precipitation measurements and offer spatial resolutions of 1km2 to several km2. This resolution is still insufficient to meet the relevant scales of urban hydrology (e.g. Berne et al. 2004; Emmanuel et al., 2011, Schellart et al., in press). Higher spatial resolution rainfall measurements can be provided by X-band radars, especially at short range where attenuation is not yet a major factor. At the Cabauw Experimental Site for Atmospheric Research (CESAR), an X-band Doppler polarimetric radar has been installed as well as a dense network of rain gauges (Leijnse et al., 2010). Data from the C-band Doppler radar at 25 km distance are also available for this site. A network of 11 rain gauges is to be installed in the city area as well as a network of water level sensors in the stormwater sewers. A selection of rain events is analysed based on the available rainfall measurement instruments for this site. The events are used as input into a hydrodynamic model of the sewer system of the city of Utrecht, located between CESAR and the C-band radar site. The effect of different spatial rainfall data resolutions and of rainfall data uncertainty on hydrological response will be analysed for various sizes of catchments within the Utrecht sewer system.

  5. Detecting Rainfall Extreme Fields and Their Scaling Using Weather Radar Data

    NASA Astrophysics Data System (ADS)

    Hamidi, A.; Devineni, N.; Zahraei, A.; Khanbilvardi, R.

    2014-12-01

    Information on the probability of extreme rainfall events of various durations is required for hydraulic design in order to control storm runoff. Such information is usually expressed as a relationship between Intensity-Duration-Frequency (IDF) of extreme rainfall. The general IDF curve approach assumes a stationary climate and typically is regionalized based on small number of gauges. However, with the ongoing accumulation of weather radar records, radar-rainfall data represent an alternative to gauging data providing much needed spatial resolution. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. The Next Generation Weather Radar system (NEXRAD) comprises of 160 Weather Surveillance Radar-1988 Doppler (WSR-88D) sites throughout the United States and at selected overseas locations. Stage IV is a national multi-sensor radar product from NCEP, mosaicked from the regional multi-sensor analyses with 4km×4km and 1h resolution of space and time respectively. In the current study, 11 years of HRAP (Hydrologic Rainfall Analysis Project) gridded Stage IV radar data is employed to generate a relationship between intensity, duration, frequency and the storm exposed area of New York Metropolitan area covering almost 30,000 km2 of the most populous cities at the east part of United States. We investigate the statistical properties of the spatial manifestation of the rainfall exceedances and present the scaling phenomena of contiguous flooded areas as a result of large scale organization of storms. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional analysis can be developed. In this project, we explore a non-parametric multivariate approach

  6. Application of weather radar CAPPI data to verify NWP rainfall accumulation data

    NASA Astrophysics Data System (ADS)

    Bassan, José Marcio; Martins, João Eduardo Machado Perea; Sugahara, Shigetoshi; da Silveira, Reinaldo Bomfim

    2015-12-01

    This study presents a method for using the CAPPI data from a weather radar to verify forecasts of 24 h accumulated precipitation from a numerical weather prediction (NWP) model, during 2010-2012. The radar used in this study consisted of a 2° beam width, Doppler and single polarization, S-band radar, located at the Meteorological Research Institute (IPMET) of Sao Paulo State University, Bauru, Sao Paulo, Brazil. A tuned version of the Eta model was used in the verification, though any model could be used with a few minor adaptations. The model, used actively at IPMET, had a horizontal grid spacing of 10 km, and was defined with the lateral boundary conditions from the Global Circulation Model of the Center for Weather Forecasting and Climate Research of the Brazilian Institute for Space Research. A linear correction was applied to the radar data, using selected rain gauges from the state of Sao Paulo's meteorological observation network, to create a reference series for both radar and NWP quantitative precipitation estimates. The reference data were used to verify the rainfall rates forecasted with the NWP, in terms of both their spatial distribution and the rainfall quantity at ground level. The results agreed well with the specific ranges of rainfall values, but there were situations where the radar data presented limitations for the verification. Ways in which to improve the methodology presented here are discussed. The current study provides an opportunity to use a high-resolution data set to verify predicted rainfall across a large spatial coverage, particularly in places which lack rain observational data.

  7. Polarimetric rainfall retrieval from a C-Band weather radar in a tropical environment (The Philippines)

    NASA Astrophysics Data System (ADS)

    Crisologo, I.; Vulpiani, G.; Abon, C. C.; David, C. P. C.; Bronstert, A.; Heistermann, Maik

    2014-11-01

    We evaluated the potential of polarimetric rainfall retrieval methods for the Tagaytay C-Band weather radar in the Philippines. For this purpose, we combined a method for fuzzy echo classification, an approach to extract and reconstruct the differential propagation phase, Φ DP , and a polarimetric self-consistency approach to calibrate horizontal and differential reflectivity. The reconstructed Φ DP was used to estimate path-integrated attenuation and to retrieve the specific differential phase, K DP . All related algorithms were transparently implemented in the Open Source radar processing software wradlib. Rainfall was then estimated from different variables: from re-calibrated reflectivity, from re-calibrated reflectivity that has been corrected for path-integrated attenuation, from the specific differential phase, and from a combination of reflectivity and specific differential phase. As an additional benchmark, rainfall was estimated by interpolating the rainfall observed by rain gauges. We evaluated the rainfall products for daily and hourly accumulations. For this purpose, we used observations of 16 rain gauges from a five-month period in the 2012 wet season. It turned out that the retrieval of rainfall from K DP substantially improved the rainfall estimation at both daily and hourly time scales. The measurement of reflectivity apparently was impaired by severe miscalibration while K DP was immune to such effects. Daily accumulations of rainfall retrieved from K DP showed a very low estimation bias and small random errors. Random scatter was, though, strongly present in hourly accumulations.

  8. ESTIMATING RAINFALL INTENSITIES FROM WEATHER RADAR DATA: THE SCALE DEPENDENCY PROBLEM 1490

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Meteorological radar is a remote sensing system that provides rainfall estimations at high spatial and temporal resolution. The radar-based rainfall intensities (R) are calculated from the observed radar reflectivities (Z). In this paper we explore scale-dependency of the power-law Z-R parameters w...

  9. Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

    NASA Astrophysics Data System (ADS)

    Zhu, D.; Xuan, Y.; Cluckie, I.

    2014-01-01

    Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the upper Medway catchment of southeast England using the UK NIMROD radar rainfall estimates, using three hydrological models based upon three very different structures (e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF). We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

  10. Hydrological appraisal of operational weather radar rainfall estimates in the context of different modelling structures

    NASA Astrophysics Data System (ADS)

    Zhu, D.; Xuan, Y.; Cluckie, I.

    2013-08-01

    Radar rainfall estimates have become increasingly available for hydrological modellers over recent years, especially for flood forecasting and warning over poorly gauged catchments. However, the impact of using radar rainfall as compared with conventional raingauge inputs, with respect to various hydrological model structures, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of the Upper Medway catchment of Southeast England using the UK NIMROD radar rainfall estimates using three hydrological models based upon three very different structures, e.g. a physically based distributed MIKE SHE model, a lumped conceptual model PDM and an event-based unit hydrograph model PRTF. We focused on the sensitivity of simulations in relation to the storm types and various rainfall intensities. The uncertainty in radar-rainfall estimates, scale effects and extreme rainfall were examined in order to quantify the performance of the radar. We found that radar rainfall estimates were lower than raingauge measurements in high rainfall rates; the resolutions of radar rainfall data had insignificant impact at this catchment scale in the case of evenly distributed rainfall events but was obvious otherwise for high-intensity, localised rainfall events with great spatial heterogeneity. As to hydrological model performance, the distributed model had consistent reliable and good performance on peak simulation with all the rainfall types tested in this study.

  11. Evaluation of radar and automatic weather station data assimilation for a heavy rainfall event in southern China

    NASA Astrophysics Data System (ADS)

    Hou, Tuanjie; Kong, Fanyou; Chen, Xunlai; Lei, Hengchi; Hu, Zhaoxia

    2015-07-01

    To improve the accuracy of short-term (0-12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System (HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting (WRF-ARW) model and the Advanced Regional Prediction System (ARPS) three-dimensional variational data assimilation (3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station (AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting (QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to 9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6-9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score (FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.

  12. Quasi-real time estimation of intense rainfall rates from weather radar

    NASA Astrophysics Data System (ADS)

    Libertino, Andrea; Allamano, Paola; Claps, Pierluigi; Cremonini, Roberto; Laio, Francesco

    2015-04-01

    Rainfall intensity estimation from radar is known to be prone to different sources of uncertainty, both in the detection and in the processing phase. These sources of uncertainty are especially relevant when severe rainfall rates are considered, thus calling for the adoption of advanced methods for the estimation of the rainfall rate from radar observations. We introduce a quasi-real time procedure for the adaptive estimation of the coefficients of the Z-R relation that links radar reflectivity to rainfall rate. The proposed quasi-real time calibration can grant Z-R relationships consistent with the evolution of the event while the use of a spatially adaptive approach makes the technique amenable to be applied in large areas with complex orography. The aim is to define a simple and operative methodology suitable for a systematic and possibly unsupervised application, capable to reconstruct the whole spectrum of intensities occurred during an intense rainfall event. We propose to readjust the power-law equation commonly used to transform reflectivity to rainfall intensity at each time step, calibrating its parameters by means of Z-R pairs collected in the time proximity of the considered instant. Z-R data are filtered with a reflectivity threshold, which varies in time, in order to discriminate between the presence and absence of rainfall. For every location, the spatial calibration domain is limited to the rain gauges belonging to a neighbourhood. Z-R coefficients are estimated for each location and each time step by minimizing the standard deviation between observed and estimated rainfall, through a non-linear procedure. The case study includes a set of 16 severe rainfall events occurred in the north-west of Italy. The technique outperforms the classical estimation methods for most of the analysed events and shows significant potential for operational uses. The determination coefficient undergoes up to 30% improvements and the BIAS values are reduced, for

  13. Gridded radar rainfall product for comparison with model rainfall

    NASA Astrophysics Data System (ADS)

    Jyothi, K. Amar; Devajyoti, D.; Kumar, D. Preveen; Rajagopal, E. N.; Rao, T. Narayana

    2016-05-01

    A tool for the entire Indian weather radar network using the static composite QI (Quality Index) map is generated. Various customized modules are used for this generation of the radar mosaic. The characterization of quality of DWR (Doppler weather Radar) data in terms of their QI is essential for assimilating the data into NWP (Numerical Weather Prediction) models. The static QI maps give a quick overview about the inherent errors in the DWR data. Quality control algorithms are applied for the generation of composite QI. The near real time access to the DWR data at NCMRWF enables the generation of an accumulated gridded radar rainfall product. This gridded rainfall map is useful for generating products like high resolution rainfall product, QPE (quantitative precipitation estimate) and for other applications. Results of some case studies shall be presented.

  14. Comparison of radar data versus rainfall data.

    PubMed

    Espinosa, B; Hromadka, T V; Perez, R

    2015-01-01

    Doppler radar data are increasingly used in rainfall-runoff synthesis studies, perhaps due to radar data availability, among other factors. However, the veracity of the radar data are often a topic of concern. In this paper, three Doppler radar outcomes developed by the United States National Weather Service at three radar sites are examined and compared to actual rain gage data for two separate severe storm events in order to assess accuracy in the published radar estimates of rainfall. Because the subject storms were very intense rainfall events lasting approximately one hour in duration, direct comparisons between the three radar gages themselves can be made, as well as a comparison to rain gage data at a rain gage location subjected to the same storm cells. It is shown that topographic interference with the radar outcomes can be a significant factor leading to differences between radar and rain gage readings, and that care is needed in calibrating radar outcomes using available rain gage data in order to interpolate rainfall estimates between rain gages using the spatial variation observed in the radar readings. The paper establishes and describes•the need for "ground-truthing" of radar data, and•possible errors due to topographic interference. PMID:26649276

  15. Comparison of radar data versus rainfall data

    PubMed Central

    Espinosa, B.; Hromadka, T.V.; Perez, R.

    2015-01-01

    Doppler radar data are increasingly used in rainfall-runoff synthesis studies, perhaps due to radar data availability, among other factors. However, the veracity of the radar data are often a topic of concern. In this paper, three Doppler radar outcomes developed by the United States National Weather Service at three radar sites are examined and compared to actual rain gage data for two separate severe storm events in order to assess accuracy in the published radar estimates of rainfall. Because the subject storms were very intense rainfall events lasting approximately one hour in duration, direct comparisons between the three radar gages themselves can be made, as well as a comparison to rain gage data at a rain gage location subjected to the same storm cells. It is shown that topographic interference with the radar outcomes can be a significant factor leading to differences between radar and rain gage readings, and that care is needed in calibrating radar outcomes using available rain gage data in order to interpolate rainfall estimates between rain gages using the spatial variation observed in the radar readings. The paper establishes and describes•the need for “ground-truthing” of radar data, and•possible errors due to topographic interference. PMID:26649276

  16. Real-time estimation of rainfall fields using radar rainfall and rain gage data

    NASA Astrophysics Data System (ADS)

    Seo, D.-J.

    1998-07-01

    New attempts at real-time estimation of rainfall fields using rain gage and radar rainfall data are reported. Based on multiplicative decomposition of expectation of rainfall into conditional expectation of rainfall given raining and probability of rainfall, the estimation procedures explicitly account for both within-storm variability of rainfall and variability due to fractional coverage of rainfall. As a result, in addition to the accuracy of radar rainfall data in estimating rainfall given that rainfall is successfully detected, that in discerning rainfall from no rainfall can also be taken into account. To evaluate the estimation procedures, cross validation was performed using hourly radar rainfall data from the Tulsa, Oklahoma, Weather Surveillance Radar-1988 Doppler version (WSR-88D) and hourly rain gage data under the radar umbrella.

  17. Spaceborne weather radar

    NASA Technical Reports Server (NTRS)

    Meneghini, Robert; Kozu, Toshiaki

    1990-01-01

    The present work on the development status of spaceborne weather radar systems and services discusses radar instrument complementarities, the current forms of equations for the characterization of such aspects of weather radar performance as surface and mirror-image returns, polarimetry, and Doppler considerations, and such essential factors in spaceborne weather radar design as frequency selection, scanning modes, and the application of SAR to rain detection. Attention is then given to radar signal absorption by the various atmospheric gases, rain drop size distribution and wind velocity determinations, and the characteristics of clouds, as well as the range of available estimation methods for backscattering, single- and dual-wavelength attenuation, and polarimetric and climatological characteristics.

  18. Research relative to weather radar measurement techniques

    NASA Technical Reports Server (NTRS)

    Smith, Paul L.

    1992-01-01

    Research relative to weather radar measurement techniques, which involves some investigations related to measurement techniques applicable to meteorological radar systems in Thailand, is reported. A major part of the activity was devoted to instruction and discussion with Thai radar engineers, technicians, and meteorologists concerning the basic principles of radar meteorology and applications to specific problems, including measurement of rainfall and detection of wind shear/microburst hazards. Weather radar calibration techniques were also considered during this project. Most of the activity took place during two visits to Thailand, in December 1990 and February 1992.

  19. Assessing the role of spatial rainfall variability on watersheds response using weather radar A case study in the Gard region, France

    NASA Astrophysics Data System (ADS)

    Anggraheni, Evi; Payrastre, Olivier; Emmanuel, Isabelle; Andrieu, Herve

    2014-05-01

    The consideration of spatial rainfall variability in hydrological modeling is not only an important scientific issue but also, with the current development of high resolution rainfall data from weather radars, an increasing request from managers of sewerage networks and from flood forecasting services. Although the literature on this topic is already significant, at this time the conclusions remain contrasted. The impact of spatial rainfall variability on the hydrological responses appears to highly depend both on the organization of rainfall fields and on the watershed characteristics. The objective of the study presented here is to confirm and analyze the high impact of spatial rainfall variability in the specific context of flash floods. The case study presented is located in the Gard region in south east of France and focuses on four events which occurred on 13 different watersheds in 2008. The hydrological behaviors of these watersheds have been represented by the distributed rainfall - runoff model CINECAR, which already proved to well represent the hydrological responses in this region (Naulin et al., 2013). The influence of spatial rainfall variability has been studied here by considering two different rainfall inputs: radar data with a resolution of 1 km x 1 km and the spatial average rainfall over the catchment. First, the comparison between simulated and measured hydrographs confirms the good performances of the model for intense rainfall events, independently of the level of spatial rainfall variability of these events. Secondly, the simulated hydrographs obtained from radar data are taken as reference and compared to those obtained from the average rainfall inputs by computing two values: the time difference and the difference of magnitude between the simulated peaks discharge. The results highly depend on the rainfall event considered, and on the level of organization of the spatial rainfall variability. According to the model, the behavior of the

  20. Polarimetric Doppler Weather Radar

    NASA Astrophysics Data System (ADS)

    Bringi, V. N.; Chandrasekar, V.

    2001-10-01

    This work provides a detailed introduction to the principles of Doppler and polarimetric radar, focusing in particular on their use in the analysis of weather systems. The authors first discuss underlying topics such as electromagnetic scattering, polarization, and wave propagation. They then detail the engineering aspects of pulsed Doppler polarimetric radar, before examining key applications in meteorology and remote sensing. The book is aimed at graduate students of electrical engineering and atmospheric science as well as practitioners involved in the applications of polarimetric radar.

  1. New weather radar coming

    NASA Astrophysics Data System (ADS)

    Maggs, William Ward

    What would you call the next generation of radar for severe weather prediction? NEXRAD, of course. A prototype for the new system was recently completed in Norman, Okla., and by the early 1990s up to 195 stations around the United States will be tracking dangerous weather and sending faster, more accurate, and more detailed warnings to the public.NEXRAD is being built for the Departments of Commerce, Transportation, and Defense by the Unisys Corporation under a $450 million contract signed in December 1987. Th e system will be used by the National Weather Service, the Federal Aviation Administration (FAA), and the U.S. Air Force and Navy. The NEXRAD radar tower in Norman is expected to be operational in October.

  2. Terminal Doppler weather radar

    NASA Astrophysics Data System (ADS)

    Michelson, M.; Shrader, W. W.; Wieler, J. G.

    1990-02-01

    The terminal Doppler weather radar (TDWR) system, now under development, will provide automatic detection of microbursts and low-level wind shear. This paper discusses the TDWR performance parameters and describes its structural elements, including the antenna subsystem, the transmitter, the receiver/exciter, the digital signal processor, and the radar product generator/remote monitoring subsystem. Attention is also given to the processes of the base data formation, point target removal, signal-to-noise thresholding, and velocity de-aliasing and to the TDWR algorithms and displays. A schematic diagram of the TDWR system is presented.

  3. Probabilistic forecasts based on radar rainfall uncertainty

    NASA Astrophysics Data System (ADS)

    Liguori, S.; Rico-Ramirez, M. A.

    2012-04-01

    The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system [4] developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at

  4. Real-time radar rainfall estimation

    NASA Astrophysics Data System (ADS)

    Anagnostou, Emmanouil Nikolaos

    1997-08-01

    This research reports on several aspects of real-time monitoring of the spatial and temporal distribution of rainfall from ground-based weather radar. Optimization of the performance of the National Weather Service's Precipitation Processing Subsystem (PPS) is the first objective. This is achieved by developing a calibration procedure which simultaneously estimates the optimal parameter values by providing a global assessment of the system's performance. Evaluation of the system is based on a data set consisting of two months of radar reflectivity measurements, and hourly raingage rainfall accumulations, from the Melbourne, Florida WSR-88D site. Radar-raingage root mean square (RMS) difference reduction up to 20% with respect to the default system parameter values is demonstrated. Investigation of statistical procedures for real-time adjustment of the mean-field systematic radar rainfall error is the second objective. For this purpose, a data- based Monte Carlo simulation experiment is performed. The study uses an extensive data set of hourly radar rainfall products and raingage accumulations from the Tulsa, Oklahoma WSR-88D site. This intercomparison study concluded to a bias procedure which overall appeared to perform better than the other. The main results from this research are: (1) statistical methods with optimal error model parameters perform significantly better than using only bias observations, and (2) bias adjustment is mostly effective in cold season precipitation measurements. Final objective of this research is development of a new real-time radar rainfall estimation algorithm. The new processing steps introduced in this algorithm are beam- height effect correction, vertical integration, rain classification, and continuous range effect correction. Additionally, the algorithm applies advection correction at the gridded rainfall rates to minimize the temporal sampling effect, and its calibration is cast in a recursive formulation with parameters

  5. Examination on accuracy of the radar rainfall estimated by using Korean dual-pol radar rainfall estimation algorithm

    NASA Astrophysics Data System (ADS)

    Yoon, Jungsoo; Choi, Dayoung; Suk, Mi-Kyung; Nam, Kyung-Yeub; Lee, Sangmi; Ko, Jeong-Seok

    2016-04-01

    Weather Radar Center (WRC) in Korea Meteorological Administration (KMA) have tried to improve the accuracy of the radar rainfall. WRC introduced Radar-AWS Rainrate (RAR) algorithm in 2001 to quantitatively improve the accuracy of the radar rainfall. Whereafter, RAR algorithm have been advanced and still used to estimate the radar rainfall. WRC has developed Korean dual-pol radar rainfall estimation algorithm from 2014 when the project of constructing the dual-pol radar network was initiated. WRC therefore suggested first Korean dual-pol radar rainfall estimation equations (R(Z), R(Z, ZDR), R(ZDR, KDP), and R(KDP)) in 2014 and developed the equations in 2015. Since WRC just suggested each equation, it needs to algorithmize the equations. This study suggested Korean dual-pol radar rainfall estimation algorithm and examined on the accuracy of the radar rainfall estimated by the algorithm. The radar measurements obtained by dual-pol radars (BRI, BSL, and SBS) which were introduced in 2015 were used.

  6. INTEGRATED CONTROL OF COMBINED SEWER REGULATORS USING WEATHER RADAR

    EPA Science Inventory

    Integrated operation was simulated of ten dynamic combined sewer regulators on a Montreal interceptor. Detailed review of digital recording weather radar capabilities indicated that it is potentially the best rainfall estimation means for accomplishing the runoff prediction that ...

  7. Runoff Analysis Considering Orographical Features Using Dual Polarization Radar Rainfall

    NASA Astrophysics Data System (ADS)

    Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo

    2013-04-01

    Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is

  8. Hydrologic applications of weather radar

    NASA Astrophysics Data System (ADS)

    Seo, Dong-Jun; Habib, Emad; Andrieu, Hervé; Morin, Efrat

    2015-12-01

    By providing high-resolution quantitative precipitation information (QPI), weather radars have revolutionized hydrology in the last two decades. With the aid of GIS technology, radar-based quantitative precipitation estimates (QPE) have enabled routine high-resolution hydrologic modeling in many parts of the world. Given the ever-increasing need for higher-resolution hydrologic and water resources information for a wide range of applications, one may expect that the use of weather radar will only grow. Despite the tremendous progress, a number of significant scientific, technological and engineering challenges remain to realize its potential. New challenges are also emerging as new areas of applications are discovered, explored and pursued. The purpose of this special issue is to provide the readership with some of the latest advances, lessons learned, experiences gained, and science issues and challenges related to hydrologic applications of weather radar. The special issue features 20 contributions on various topics which reflect the increasing diversity as well as the areas of focus in radar hydrology today. The contributions may be grouped as follows: Radar QPE (Kwon et al.; Hall et al.; Chen and Chandrasekar; Seo and Krajewski; Sandford).

  9. Optimization of multiparameter radar estimates of rainfall

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Gorgucci, Eugenio; Scarchilli, Gianfranco

    1993-01-01

    The estimates of rainfall rate derived from a multiparameter radar based on reflectivity factor (R sub ZH), differential reflectivity (R sub DR), and specific differential propagation phase (R sub DP) have widely varying accuracies over the dynamic range of the natural occurrence of rainfall. This paper presents a framework to optimally combine the three estimates, R sub zH, R sub DR, and R sub DP, to derive the best estimate of rainfall using coherent multiparameter radars. The optimization procedure is demonstrated for application to multiparameter radar measurements at C band.

  10. Bias Correction of Polarimetric Variables and Uncertainty Quantification of Dual-Polarization Radar Rainfall Estimation

    NASA Astrophysics Data System (ADS)

    Yoon, J.; Suk, M. K.; Nam, K. Y.; Ko, J. S.; Kim, H. L.

    2015-12-01

    Radar rainfall is generally less than gauge rainfall and it deteriorates in the case of high rainfall. Introduction of dual-polarization radar, however, has shed some light on the problem to underestimate radar rainfall in single-polarization radar. Dual-polarization radar provides various variables such like the differential reflectivity, differential phase, specific differential phase, and correlation coefficient, etc. as well as the reflectivity. Due to the advantage of dual-polarization radar providing various information available on the precipitation, the quality of the radar rainfall becomes much higher. Total five dual-polarization radars (Baengnyeongdo, Yongin-Testbed, Bislsan, Sobaeksan and Mohusan Radar) were introduced in Korea until now and the project, "Development and application of Cross governmental dual-pol radar harmonization", is on the way. Weather Radar Center (WRC), Korea Meteorological Adminstration (KMA) has played a leading role in the dual-polarization radar technology in Korea. WRC has been researching the quality control (QC) for the polarimetric variables, the classification of the precipitation, the radar rainfall estimation algorithm, and the composite dual-polarimetric varaiables field, etc. WRC (2014) suggested Korean polarimetric radar variables relation (Z-ZDR relation and Z-KDP relation) and Korean radar rainfall estimation algorithm (R(Z, ZDR) WRC algorithm). This study examined on the six radar rainfall estimation algorithms including R(Z, ZDR) WRC algorithm and corrected the bias of polarimetric variables using Korean polarimetric variables relation. Plus, this study quantified the uncertainty of the radar rainfall estimated from six algorithms before and after the correction. As a result, the quality of the radar rainfall after the correction improved and Korean radar rainfall estimation algorithm had the best quality among the algorithms using the Z and ZDR,

  11. Efficient Ways to Learn Weather Radar Polarimetry

    ERIC Educational Resources Information Center

    Cao, Qing; Yeary, M. B.; Zhang, Guifu

    2012-01-01

    The U.S. weather radar network is currently being upgraded with dual-polarization capability. Weather radar polarimetry is an interdisciplinary area of engineering and meteorology. This paper presents efficient ways to learn weather radar polarimetry through several basic and practical topics. These topics include: 1) hydrometeor scattering model…

  12. Analysis of spatial variability of extreme rainfall at radar subpixel scale using IDF curves

    NASA Astrophysics Data System (ADS)

    Peleg, Nadav; Marra, Francesco; Fatichi, Simone; Paschalis, Athanasios; Molnar, Peter; Burlando, Paolo

    2016-04-01

    Extreme rainfall is quantified in engineering practice using Intensity-Duration-Frequency curves (IDFs) that are traditionally derived from rain-gauges and, more recently, also from weather radars. These instruments measure rainfall at different spatial scales: rain-gauge samples rainfall at the point scale while weather radar averages precipitation over a relatively large area, generally around 1 km2. As such, a radar derived IDF curve is representative of the mean areal rainfall over a given radar pixel and neglects the within-pixel rainfall variability. In this study, we quantify subpixel variability of extreme rainfall by using a novel space-time rainfall generator (STREAP model) that downscales in space the rainfall within a given radar pixel. The study was conducted using a long radar data record (23 years) and a very dense rain-gauge network in the Eastern Mediterranean area. Radar-IDF curves, together with an ensemble of point-based IDF curves representing the radar subpixel extreme rainfall variability, were developed fitting GEV distributions to annual rainfall maxima. It was found that the mean areal extreme rainfall derived from the radar underestimate most of the extreme values computed for point locations within the radar pixel. The subpixel variability of extreme rainfall was found to increase with longer return periods and shorter durations. For the longer return periods, a considerable enhancement of extreme rainfall variability was found when stochastic (natural) climate variability was taken into account. Bounding the range of the subpixel extreme rainfall derived from radar-IDF can be of major importance for applications that require very local estimates of rainfall extremes.

  13. Past-time Radar Rainfall Estimates using Radar AWS Rainrate system with Local Gauge Correction method

    NASA Astrophysics Data System (ADS)

    Choi, D.; Lee, M. H.; Suk, M. K.; Nam, K. Y.; Hwang, J.; Ko, J. S.

    2015-12-01

    The Weather Radar Center at Korea Meteorological Administration (KMA) has radar network for warnings for heavy rainfall and severe storms. We have been operating an operational real-time adjusted the Radar-Automatic Weather Station (AWS) Rainrate (RAR) system developed by KMA in 2006 for providing radar-based quantitative precipitation estimation (QPE) to meteorologists. This system has several uncertainty in estimating precipitation by radar reflectivity (Z) and rainfall intensity (R) relationship. To overcome uncertainty of the RAR system and improve the accuracy of QPE, we are applied the Local Gauge Correction (LGC) method which uses geo-statistical effective radius of errors of the QPE to RAR system in 2012. According to the results of previous study in 2014 (Lee et al., 2014), the accuracy of the RAR system with LGC method improved about 7.69% than before in the summer season of 2012 (from June to August). It has also improved the accuracy of hydrograph when we examined the accuracy of flood simulation using hydrologic model and data derived by the RAR system with LGC method. We confirmed to have its effectiveness through these results after the application of LGC method. It is required for high quality data of long term to utilize in hydrology field. To provide QPE data more precisely and collect past-time data, we produce that calculated by the RAR system with LGC method in the summer season from 2006 to 2009 and investigate whether the accuracy of past-time radar rainfall estimation enhance or not. Keywords : Radar-AWS Rainrate system, Local gauge correction, past-time Radar rainfall estimation Acknowledgements : This research is supported by "Development and application of Cross governmental dual-pol radar harmonization (WRC-2013-A-1)" project of the Weather Radar Center, Korea Meteorological Administration in 2015.

  14. Improvement of rainfall and flood forecasts by blending ensemble NWP rainfall with radar prediction considering orographic rainfall

    NASA Astrophysics Data System (ADS)

    Yu, Wansik; Nakakita, Eiichi; Kim, Sunmin; Yamaguchi, Kosei

    2015-12-01

    Many basins in Japan are characterized by steep mountainous regions, generating orographic rainfall events. Orographic rainfall may cause localized heavy rainfall to induce flash floods and sediment disasters. However, the accuracy of radar-based rainfall prediction was not enough because of the complex geographical pattern of the mountainous areas. In order to reduce damage due to localized heavy rainfall, characteristics of orographic rainfall must be identified into a short-term rainfall prediction procedure. The accuracy of radar-based rainfall prediction performs best for very short lead time, however the accuracy of radar prediction rapidly decreases with increasing lead times. At longer lead times, higher accuracy QPFs are produced by Numerical Weather Prediction (NWP) models, which solve the dynamics and physics of the atmosphere. This study proposes hybrid blending system of ensemble information from radar-based prediction and numerical weather prediction (NWP) to improve the accuracy of rainfall and flood forecasting. First, an improved radar image extrapolation method, which is comprised of the orographic rainfall identification and the error ensemble scheme, is introduced. Then, ensemble NWP outputs are updated based on mean bias of the error fields considering error structure. Finally, the improved radar-based prediction and updated NWP rainfall considering bias correction are blended dynamically with changing weight functions, which are computed from the expected skill of each radar prediction and updated NWP rainfall. The proposed method is verified temporally and spatially through a target event and is applied to the hybrid flood forecasting for updating with 1 h intervals. The newly proposed method shows sufficient reproducibility in peak discharge value, and could reduce the width of ensemble spread, which is expressed as the uncertainty, in the flood forecasting. Our study is carried out and verified using the largest flood event by typhoon

  15. Radar Rainfall Estimation for Ground Validation Studies of the Tropical Rainfall Measuring Mission.

    NASA Astrophysics Data System (ADS)

    Ciach, Grzegorz J.; Krajewski, Witold F.; Anagnostou, Emmanouil N.; Baeck, Mary L.; Smith, James A.; McCollum, Jeffrey R.; Kruger, Anton

    1997-06-01

    This study presents a multicomponent rainfall estimation algorithm, based on weather radar and rain gauge network, that can be used as a ground-based reference in the satellite Tropical Rainfall Measuring Mission (TRMM). The essential steps are constructing a radar observable, its nonlinear transformation to rainfall, interpolation to rectangular grid, constructing several timescale accumulations, bias adjustment, and merging of the radar rainfall estimates and rain gauge data. Observations from a C-band radar in Darwin, Australia, and a local network of 54 rain gauges were used to calibrate and test the algorithm. A period of 25 days was selected, and the rain gauges were split into two subsamples to apply cross-validation techniques.A Z-R relationship with continuous range dependence and a temporal interpolation scheme that accounts for the advection effects is applied. An innovative methodology was used to estimate the algorithm controlling parameters. The model was globally optimized by using an objective function on the level of the final products. This is equivalent to comparing hundreds of Z-R relationships using a uniform and representative performance criterion. The algorithm performance is fairly insensitive to the parameter variations around the optimum. This suggests that the accuracy limit of the radar rainfall estimation based on power-law Z-R relationships has been reached. No improvement was achieved by using rain regime classification prior to estimation.

  16. Enhanced Weather Radar (EWxR) System

    NASA Technical Reports Server (NTRS)

    Kronfeld, Kevin M. (Technical Monitor)

    2003-01-01

    An airborne weather radar system, the Enhanced Weather Radar (EWxR), with enhanced on-board weather radar data processing was developed and tested. The system features additional weather data that is uplinked from ground-based sources, specialized data processing, and limited automatic radar control to search for hazardous weather. National Weather Service (NWS) ground-based Next Generation Radar (NEXRAD) information is used by the EWxR system to augment the on-board weather radar information. The system will simultaneously display NEXRAD and on-board weather radar information in a split-view format. The on-board weather radar includes an automated or hands-free storm-finding feature that optimizes the radar returns by automatically adjusting the tilt and range settings for the current altitude above the terrain and searches for storm cells near the atmospheric 0-degree isotherm. A rule-based decision aid was developed to automatically characterize cells as hazardous, possibly-hazardous, or non-hazardous based upon attributes of that cell. Cell attributes are determined based on data from the on-board radar and from ground-based radars. A flight path impact prediction algorithm was developed to help pilots to avoid hazardous weather along their flight plan and their mission. During development the system was tested on the NASA B757 aircraft and final tests were conducted on the Rockwell Collins Sabreliner.

  17. Propagation of radar rainfall uncertainty in urban flood simulations

    NASA Astrophysics Data System (ADS)

    Liguori, Sara; Rico-Ramirez, Miguel

    2013-04-01

    , 2010. Review of the different sources of uncertainty in single polarization radar-based estimates of rainfall. Surveys in Geophysics 31: 107-129. [4] Rossa A, Liechti K, Zappa M, Bruen M, Germann U, Haase G, Keil C, Krahe P, 2011. The COST 731 Action: A review on uncertainty propagation in advanced hydrometeorological forecast systems. Atmospheric Research 100, 150-167. [5] Rossa A, Bruen M, Germann U, Haase G, Keil C, Krahe P, Zappa M, 2010. Overview and Main Results on the interdisciplinary effort in flood forecasting COST 731-Propagation of Uncertainty in Advanced Meteo-Hydrological Forecast Systems. Proceedings of Sixth European Conference on Radar in Meteorology and Hydrology ERAD 2010. [6] Germann U, Berenguer M, Sempere-Torres D, Zappa M, 2009. REAL - ensemble radar precipitation estimation for hydrology in a mountainous region. Quarterly Journal of the Royal Meteorological Society 135: 445-456. [8] Bowler NEH, Pierce CE, Seed AW, 2006. STEPS: a probabilistic precipitation forecasting scheme which merges and extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society 132: 2127-2155. [9] Zappa M, Rotach MW, Arpagaus M, Dorninger M, Hegg C, Montani A, Ranzi R, Ament F, Germann U, Grossi G et al., 2008. MAP D-PHASE: real-time demonstration of hydrological ensemble prediction systems. Atmospheric Science Letters 9, 80-87. [10] Liguori S, Rico-Ramirez MA. Quantitative assessment of short-term rainfall forecasts from radar nowcasts and MM5 forecasts. Hydrological Processes, accepted article. DOI: 10.1002/hyp.8415 [11] Liguori S, Rico-Ramirez MA, Schellart ANA, Saul AJ, 2012. Using probabilistic radar rainfall nowcasts and NWP forecasts for flow prediction in urban catchments. Atmospheric Research 103: 80-95. [12] Harrison DL, Driscoll SJ, Kitchen M, 2000. Improving precipitation estimates from weather radar using quality control and correction techniques. Meteorological Applications 7: 135-144. [13] Harrison DL, Scovell RW, Kitchen

  18. SUB-PIXEL RAINFALL VARIABILITY AND THE IMPLICATIONS FOR UNCERTAINTIES IN RADAR RAINFALL ESTIMATES

    EPA Science Inventory

    Radar estimates of rainfall are subject to significant measurement uncertainty. Typically, uncertainties are measured by the discrepancies between real rainfall estimates based on radar reflectivity and point rainfall records of rain gauges. This study investigates how the disc...

  19. Impacts of Characteristics of Errors in Radar Rainfall Estimates for Rainfall-Runoff Simulation

    NASA Astrophysics Data System (ADS)

    KO, D.; PARK, T.; Lee, T. S.; Shin, J. Y.; Lee, D.

    2015-12-01

    For flood prediction, weather radar has been commonly employed to measure the amount of precipitation and its spatial distribution. However, estimated rainfall from the radar contains uncertainty caused by its errors such as beam blockage and ground clutter. Even though, previous studies have been focused on removing error of radar data, it is crucial to evaluate runoff volumes which are influenced primarily by the radar errors. Furthermore, resolution of rainfall modeled by previous studies for rainfall uncertainty analysis or distributed hydrological simulation are quite coarse to apply to real application. Therefore, in the current study, we tested the effects of radar rainfall errors on rainfall runoff with a high resolution approach, called spatial error model (SEM). In the current study, the synthetic generation of random and cross-correlated radar errors were employed as SEM. A number of events for the Nam River dam region were tested to investigate the peak discharge from a basin according to error variance. The results indicate that the dependent error brings much higher variations in peak discharge than the independent random error. To further investigate the effect of the magnitude of cross-correlation between radar errors, the different magnitudes of spatial cross-correlations were employed for the rainfall-runoff simulation. The results demonstrate that the stronger correlation leads to higher variation of peak discharge and vice versa. We conclude that the error structure in radar rainfall estimates significantly affects on predicting the runoff peak. Therefore, the efforts must take into consideration on not only removing radar rainfall error itself but also weakening the cross-correlation structure of radar errors in order to forecast flood events more accurately. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which

  20. Reducing Spaceborne-Doppler-Radar Rainfall-Velocity Error

    NASA Technical Reports Server (NTRS)

    Tanelli, Simone; Im, Eastwood; Durden, Stephen L.

    2008-01-01

    A combined frequency-time (CFT) spectral moment estimation technique has been devised for calculating rainfall velocity from measurement data acquired by a nadir-looking spaceborne Doppler weather radar system. Prior spectral moment estimation techniques used for this purpose are based partly on the assumption that the radar resolution volume is uniformly filled with rainfall. The assumption is unrealistic in general but introduces negligible error in application to airborne radar systems. However, for spaceborne systems, the combination of this assumption and inhomogeneities in rainfall [denoted non-uniform beam filling (NUBF)] can result in velocity measurement errors of several meters per second. The present CFT spectral moment estimation technique includes coherent processing of a series of Doppler spectra generated in a standard manner from data over measurement volumes that are partially overlapping in the along-track direction. Performance simulation of this technique using high-resolution data from an airborne rain-mapping radar shows that a spaceborne Ku-band Doppler radar operating at signal-to-noise ratios greater than 10 dB can achieve root-mean-square accuracy between 0.5 and 0.6 m/s in vertical-velocity estimates.

  1. Airborne Differential Doppler Weather Radar

    NASA Technical Reports Server (NTRS)

    Meneghini, R.; Bidwell, S.; Liao, L.; Rincon, R.; Heymsfield, G.; Hildebrand, Peter H. (Technical Monitor)

    2001-01-01

    The Precipitation Radar aboard the Tropical Rain Measuring Mission (TRMM) Satellite has shown the potential for spaceborne sensing of snow and rain by means of an incoherent pulsed radar operating at 13.8 GHz. The primary advantage of radar relative to passive instruments arises from the fact that the radar can image the 3-dimensional structure of storms. As a consequence, the radar data can be used to determine the vertical rain structure, rain type (convective/stratiform) effective storm height, and location of the melting layer. The radar, moreover, can be used to detect snow and improve the estimation of rain rate over land. To move toward spaceborne weather radars that can be deployed routinely as part of an instrument set consisting of passive and active sensors will require the development of less expensive, lighter-weight radars that consume less power. At the same time, the addition of a second frequency and an upgrade to Doppler capability are features that are needed to retrieve information on the characteristics of the drop size distribution, vertical air motion and storm dynamics. One approach to the problem is to use a single broad-band transmitter-receiver and antenna where two narrow-band frequencies are spaced apart by 5% to 10% of the center frequency. Use of Ka-band frequencies (26.5 GHz - 40 GHz) affords two advantages: adequate spatial resolution can be attained with a relatively small antenna and the differential reflectivity and mean Doppler signals are directly related to the median mass diameter of the snow and raindrop size distributions. The differential mean Doppler signal has the additional property that this quantity depends only on that part of the radial speed of the hydrometeors that is drop-size dependent. In principle, the mean and differential mean Doppler from a near-nadir viewing radar can be used to retrieve vertical air motion as well as the total mean radial velocity. In the paper, we present theoretical calculations for the

  2. An Improved Polarimetric Radar Rainfall Algorithm With Hydrometeor Classification Optimized For Rainfall Estimation

    NASA Astrophysics Data System (ADS)

    Cifelli, R.; Wang, Y.; Lim, S.; Kennedy, P.; Chandrasekar, V.; Rutledge, S. A.

    2009-05-01

    The efficacy of dual polarimetric radar for quantitative precipitation estimation (QPE) is firmly established. Specifically, rainfall retrievals using combinations of reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase (KDP) have advantages over traditional Z-R methods because more information about the drop size distribution and hydrometeor type are available. In addition, dual-polarization radar measurements are generally less susceptible to error and biases due to the presence of ice in the sampling volume. A number of methods have been developed to estimate rainfall from dual-polarization radar measurements. However, the robustness of these techniques in different precipitation regimes is unknown. Because the National Weather Service (NWS) will soon upgrade the WSR 88-D radar network to dual-polarization capability, it is important to test retrieval algorithms in different meteorological environments in order to better understand the limitations of the different methodologies. An important issue in dual-polarimetric rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? At Colorado State University (CSU), a "blended" algorithm has been developed and used for a number of years to estimate rainfall based on ZH, ZDR, and KDP (Cifelli et al. 2002). The rainfall estimators for each sampling volume are chosen on the basis of fixed thresholds, which maximize the measurement capability of each polarimetric variable and combinations of variables. Tests have shown, however, that the retrieval is sensitive to the calculation of ice fraction in the radar volume via the difference reflectivity (ZDP - Golestani et al. 1989) methodology such that an inappropriate estimator can be selected in situations where radar echo is

  3. Utilization of regression models for rainfall estimates using radar-derived rainfall data and rain gauge data

    NASA Astrophysics Data System (ADS)

    Sokol, Zbynĕk

    2003-07-01

    The procedure estimating hourly rainfalls by merging radar-derived rainfalls and gauge measurements is developed and tested. It uses simple linear regression, which is complemented by the normalization and correction of distribution. The data from radar Tulsa, Oklahoma, Weather Surveillance Radar-1988 Doppler version and rain gauge data from the radar domain are used. The quality of estimates is evaluated against independent rain gauges by the root-mean-square-error, bias and correlation coefficient in dependence on the density of a gauge network. The results indicate that even a sparse gauge network (about 50 gauges, i.e. 4000 km 2 per one gauge) is sufficient to improve the radar-derived rainfalls. The improvement increases with the number of gauges.

  4. Vertical and Temporal Variability of Rainfall Using a K-band Radar

    NASA Astrophysics Data System (ADS)

    Mazari, N.; Sharif, H. O.; Xie, H.; Tekeli, A. E.; Habib, E. H.; Zeitler, J.

    2012-12-01

    A vertically pointing Micro Rain Radar (MRR) was installed along a tipping bucket rain gauge at a site within a distance of 58.54 km from the nearest local National Weather Service weather radar, which have an average beam height of 552 m above ground level at the collocated gauge and MRR site. The MRR data were collected at two different gate height resolutions, 35 and 100 meters. The results showed that weather radar underestimated rainfall by 30 to 40% with respect to the gauge. And the MRR rainfall derived as function of Drop Size Distribution (DSD) and fall velocity (RR) was much closer to the gauge rainfall than MRR rainfall measurements derived from the same Z-R relationship used by the National Weather Service (Rz), which significantly underestimated rainfall in both height resolutions. The examination of the rainfall statistics suggested that the height resolution of 100 m produces better estimates especially at the third gate (centered at 300 m). MRR rain rates were highly variable during the same rainfall event or across different events. Few rainfall events showed very high rain rates at higher gates, but no bright band signature was found; thus a detailed inspection of DSDs variability with height and time is being conducted along with analysis of other MRR derived rainfall parameters to understand and capture the MRR rainfall variability and abnormalities.

  5. Singularity-sensitive merging of radar and raingauge rainfall data

    NASA Astrophysics Data System (ADS)

    Wang, Li-Pen; Willems, Patrick; Ochoa-Rodriguez, Susana; Onof, Christian

    2014-05-01

    Traditionally, urban hydrological applications relied mainly upon rain gauge data as input as these provide accurate point rainfall estimates near the ground surface. However, they cannot capture the spatial variability of rainfall, which has a significant impact on the urban hydrological system and thus on the modelling of urban pluvial flooding. Thanks to the development of radar technology, weather radar has been playing an increasingly important role in urban hydrology. Radars can survey large areas and better capture the spatial variability of the rainfall, thus improving the short term predictability of rainfall and flooding. However, the accuracy of radar measurements is in general insufficient, particularly in the case of extreme rainfall magnitudes. This has a tremendous effect on the subsequent hydraulic model outputs. In order to improve the accuracy of radar rainfall estimates while preserving their spatial description of rainfall fields, it is possible to dynamically adjust them based on rain gauge measurements. Studies on this subject have been carried out over the last few years, though most of them focus on the hydrological applications at large scales. A couple of recent research works have examined the applicability of these adjustment techniques to urban-scale hydrological applications and concluded that these techniques can effectively reduce rainfall bias, thus leading to improvements in the reproduction of hydraulic outputs (Wang et al., 2013). However, underestimation of storm peaks can still be seen after adjustment and this is particularly significant in the case of small drainage areas and for extreme rainfall magnitudes. This may be due to the fact that the underlying adjustment techniques, mainly based upon Gaussian approximations, cannot properly cope with the non-normality observed in urban scale applications. With the purpose of improving this aspect, a methodology has been developed which identifies the local extremes or

  6. Research relative to weather radar measurement techniques

    NASA Technical Reports Server (NTRS)

    Smith, Paul L.

    1992-01-01

    This grant provides for some investigations related to weather radar measurement techniques applicable to meteorological radar systems in Thailand. Quality data are needed from those systems to support TRMM and other scientific investigations. Activities carried out during a trip to the radar facilities at Phuket are described.

  7. Real-Time Flood Estimation by Using Radar Rainfall data and Distributed Rainfall-Runoff Model

    NASA Astrophysics Data System (ADS)

    Yu, P.; Chou, J.; Chiu, Y.; Yang, T.; Kuo, C.

    2011-12-01

    This study aims to establish a flood prediction model in Dajia River by using a grid-based distributed rainfall-runoff model (GDRRM) combined with the predicted QPESUMS radar rainfalls. Flood disasters caused damage to human and property. A proper flood prediction model can provide warning messages against disasters. Since the radar rainfall technology has been developed for years, it has the ability to represent the precipitation in each location. Coupling the real-time radar rainfall with the distributed rainfall-runoff model, it can be used to provide the probable flow in downstream. The study area, Dajia River basin, is located in central Taiwan. The river flow is mainly controlled by two major reservoirs, Shih-Kang Dam in downstream and Te-Chi Reservoir in upstream. Thus, three components are considered for establishing the flood prediction model. The first one is the application of radar rainfalls. The real-time and predicted (1-3hr ahead) radar rainfall data provided by the Central Weather Bureau, Taiwan were set as the input data. It can represent the actual distributed rainfalls of the basin. The second one is the estimation of reservoir inflow by using a GDRRM. The basin was divided into 1234 regular grids (1km by 1km) to exhibit the heterogeneity in the watershed. The parameters of GDRRM were generated by using DEM, Formosat-2 satellite image and soil map to represent the actual geography and physiography of each grid. With the input of real-time and predicted radar rainfall data, the inflow of Te-Chi Reservoir and Shih-Kang Dam can be calculated by using two GDRRMs respectively. The third one is the operation rules of reservoir used for simulating the outflow of the reservoirs during the flow simulation. Then, the downstream (Shih-Kang Dam) GDRRM coupled with the operation rules was used to calculate the outflow of the Te-Chi Reservoir. Thus, the flood can be predicted in advance during typhoon period. The results revealed that the flood prediction

  8. A study on WRF radar data assimilation for hydrological rainfall prediction

    NASA Astrophysics Data System (ADS)

    Liu, J.; Bray, M.; Han, D.

    2013-08-01

    Mesoscale numerical weather prediction (NWP) models are gaining more attention in providing high-resolution rainfall forecasts at the catchment scale for real-time flood forecasting. The model accuracy is however negatively affected by the "spin-up" effect and errors in the initial and lateral boundary conditions. Synoptic studies in the meteorological area have shown that the assimilation of operational observations, especially the weather radar data, can improve the reliability of the rainfall forecasts from the NWP models. This study aims at investigating the potential of radar data assimilation in improving the NWP rainfall forecasts that have direct benefits for hydrological applications. The Weather Research and Forecasting (WRF) model is adopted to generate 10 km rainfall forecasts for a 24 h storm event in the Brue catchment (135.2 km2) located in southwest England. Radar reflectivity from the lowest scan elevation of a C-band weather radar is assimilated by using the three-dimensional variational (3D-Var) data-assimilation technique. Considering the unsatisfactory quality of radar data compared to the rain gauge observations, the radar data are assimilated in both the original form and an improved form based on a real-time correction ratio developed according to the rain gauge observations. Traditional meteorological observations including the surface and upper-air measurements of pressure, temperature, humidity and wind speed are also assimilated as a bench mark to better evaluate and test the potential of radar data assimilation. Four modes of data assimilation are thus carried out on different types/combinations of observations: (1) traditional meteorological data; (2) radar reflectivity; (3) corrected radar reflectivity; (4) a combination of the original reflectivity and meteorological data; and (5) a combination of the corrected reflectivity and meteorological data. The WRF rainfall forecasts before and after different modes of data assimilation are

  9. A study of radar backscattering from water surface in response to rainfall

    NASA Astrophysics Data System (ADS)

    Liu, Xinan; Zheng, Quanan; Liu, Ren; Wang, Dan; Duncan, James H.; Huang, Shih-Jen

    2016-03-01

    In this paper, radar backscattering from a water surface in response to rainfall was studied. The paper consists of two parts. First, the spatial characteristics of raindrops in rain fields were analyzed based on published data and the response of a water surface to rainfall was experimentally studied in the laboratory. Rain-generated surface features including stalks, crowns, ring waves, and secondary drops were measured. It was found that stalks and crowns are dominant in terms of their height and energy. Second, the radar signatures of a rainfall event simultaneously observed by C band ENVISAT (European satellite), ASAR (Advanced Synthetic Aperture Radar), and ground-based weather radar in the Northwest Pacific were investigated. The relationship between the radar return intensity extracted from the C band ASAR image and the reflectivity factor (rain rate) obtained from ground-based weather radar was analyzed. For light/moderate rain (with low reflectivity factors), the radar backscattering intensity increases as the reflectivity factor increases. For heavy rain (with high reflectivity factors), the radar backscattering intensity decreases as the reflectivity factor increases. The maximum radar backscattering intensity occurs at a reflectivity factor of 45 dBZ (with rain rate of 24 mm/h). It was found that the spaceborne radar backscattering intensity strongly correlates with the average distance between the stalks on the water surface in the rain field in a nonlinear manner. The physics of the radar signatures of the rain event are explored.

  10. Rainfall and Flood Frequency Analysis Using High-Resolution Radar Rainfall Fields and Stochastic Storm Transposition

    NASA Astrophysics Data System (ADS)

    Wright, Daniel; Smith, James; Baeck, Mary Lynn

    2013-04-01

    Spatial and temporal variability of rainfall fields, and their interactions with surface, subsurface, and drainage network properties, are important drivers of flood response. 'Design storms,' which are commonly used for flood risk assessment, however, are assumed to be uniform in space and either uniform or highly idealized in time. The impacts of these and other common assumptions on estimates of flood risk are poorly understood. We present an alternative framework for flood risk assessment based on stochastic storm transposition (SST). In this framework, "storm catalogs" are derived from a ten-year high-resolution (15-minute, 1 km2) bias-corrected radar rainfall dataset for the region surrounding Charlotte, North Carolina, USA. SST-based rainfall frequency analyses are developed by resampling from these storm catalogs to synthesize the regional climatology of extreme rainfall. SST-based intensity-frequency-duration (IFD) estimates are driven by the spatial and temporal rainfall variability from weather radar observations, are specifically tailored to the chosen catchment, and do not require simplifying assumptions of storm structure. We are able to use the SST procedure to reproduce IFD estimates from conventional methods for small urban catchments in Charlotte. We further demonstrate that extreme rainfall can vary substantially in time and in space, with important flood risk implications that cannot be assessed using conventional techniques. When coupled with a physics-based distributed hydrologic model, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model, SST enables us to examine the full impact of spatial and temporal rainfall variability on flood response and flood frequency. The interactions of extreme rainfall with spatially distributed land use, soil properties, and stormwater management infrastructure are assessed for several nested urban catchments in Charlotte. Results suggest that these interactions, which cannot be fully accounted for

  11. Robust Sparse Sensing Using Weather Radar

    NASA Astrophysics Data System (ADS)

    Mishra, K. V.; Kruger, A.; Krajewski, W. F.; Xu, W.

    2014-12-01

    The ability of a weather radar to detect weak echoes is limited by the presence of noise or unwanted echoes. Some of these unwanted signals originate externally to the radar system, such as cosmic noise, radome reflections, interference from co-located radars, and power transmission lines. The internal source of noise in microwave radar receiver is mainly thermal. The thermal noise from various microwave devices in the radar receiver tends to lower the signal-to-noise ratio, thereby masking the weaker signals. Recently, the compressed sensing (CS) technique has emerged as a novel signal sampling paradigm that allows perfect reconstruction of signals sampled at frequencies lower than the Nyquist rate. Many radar and remote sensing applications require efficient and rapid data acquisition. The application of CS to weather radars may allow for faster target update rates without compromising the accuracy of target information. In our previous work, we demonstrated recovery of an entire precipitation scene from its compressed-sensed version by using the matrix completion approach. In this study, we characterize the performance of such a CS-based weather radar in the presence of additive noise. We use a signal model where the precipitation signals form a low-rank matrix that is corrupted with (bounded) noise. Using recent advances in algorithms for matrix completion from few noisy observations, we reconstruct the precipitation scene with reasonable accuracy. We test and demonstrate our approach using the data collected by Iowa X-band Polarimetric (XPOL) weather radars.

  12. Application of rainfall estimates using radar-raingauge merging techniques for hydrological simulations

    NASA Astrophysics Data System (ADS)

    Nanding, Nergui; Rico-Ramirez, Miguel Angel; Han, Dawei

    2015-04-01

    Rainfall estimates by weather radar have become an important alternative to raingauge measurements for hydrological modelling over poorly gauged catchments, due to its capability for providing spatially distributed rainfall with a high resolution in space and time. However, the potential of radar rainfall estimates has often been limited by a variety of source of errors. More recently, research has proven that by combining radar rainfall estimates with raingauge measurements it is possible to obtain better rainfall estimates that are also able to capture the spatial precipitation variability. However, the impact of using merged rainfall products as compared with conventional raingauge inputs, with respect to various hydrological model structures and catchment areas, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of different sized catchments across Northern England using rainfall inputs from different radar-raingauge merging techniques, such as Kriging with radar-based correction (KRE) and Kriging with external drift (KED). Rainfall was estimated at an hourly timescale and therefore rainfall estimates obtained from different radar-gauge merging techniques at hourly resolution are incorporated into hydrological models so that direct comparison of streamflows can be explored. The main purpose of this paper is to examine whether these merged rainfall estimates are useful as input to rainfall-runoff models over rural catchment areas, focusing on the improvement of rainfall estimates by radar-raingauge merging techniques for runoff predictions rather than on the rainfall estimates themselves in relation to the catchments sizes and storm events.

  13. Using TRMM and GPM precipitation radar for calibration of weather radars in the Philippines

    NASA Astrophysics Data System (ADS)

    Crisologo, Irene; Bookhagen, Bodo; Smith, Taylor; Heistermann, Maik

    2016-04-01

    Torrential and sustained rainfall from tropical cyclones, monsoons, and thunderstorms frequently impact the Philippines. In order to predict, assess, and measure storm impact, it is imperative to have a reliable and accurate monitoring system in place. In 2011, the Philippine Atmospheric, Geophysical, and Astronomical Services Administration (PAGASA) established a weather radar network of ten radar devices, eight of which are single-polarization S-band radars and two dual-polarization C-band radars. Because of a low-density hydrometeorological monitoring networks in the Philippines, calibration of weather radars becomes a challenging, but important task. In this study, we explore the potential of scrutinizing the calibration of ground radars by using the observations from the Tropical Rainfall Measuring Mission (TRMM). For this purpose, we compare different TRMM level 1 and 2 orbital products from overpasses over the Philippines, and compare these products to reflectivities observed by the Philippine ground radars. Differences in spatial resolution are addressed by computing adequate zonal statistics of the local radar bins located within the corresponding TRMM cell in space and time. The wradlib package (Heistermann et al. 2013; Heistermann et al. 2015) is used to process the data from the Subic S-band single-polarization weather radar. These data will be analyzed in conjunction with TRMM data for June to August 2012, three months of the wet season. This period includes the enhanced monsoon of 2012, locally called Habagat 2012, which brought sustained intense rainfall and massive floods in several parts of the country including the most populated city of Metro Manila. References Heistermann, M., Jacobi, S., Pfaff, T. (2013): Technical Note: An open source library for processing weather radar data (wradlib). Hydrol. Earth Syst. Sci., 17, 863-871, doi: 10.5194/hess-17-863-2013. Heistermann, M., S. Collis, M. J. Dixon, S. Giangrande, J. J. Helmus, B. Kelley, J

  14. Radar rainfall estimation in a hilly environment and implications for runoff modeling

    NASA Astrophysics Data System (ADS)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2010-05-01

    Radars are known for their ability to obtain a wealth of information about the spatial stormfield characteristics. Unfortunately, rainfall estimates obtained by this instrument are known to be affected by multiple sources of error. Especially for stratiform precipitation systems, the quality of radar rainfall estimates starts to decrease at relatively close ranges. In the current study the hydrological potential of weather radar is analyzed during a winter half-year for the hilly region of the Belgian Ardennes. A correction algorithm is proposed taking into account attenuation, ground clutter, anomalous propagation, the vertical profile of reflectivity (VPR) and advection. No final bias correction with respect to rain gauge data were implemented, because that does not add to a better understanding of the quality of the radar. Largest quality improvements in the radar data are obtained by ground clutter removal. The influence of VPR correction and advection depends on the precipitation system observed. Overall, the radar shows an underestimation as compared to the rain gauges, which becomes smaller after averaging at the scale of the medium-sized Ourthe catchment. Remaining differences between both devices can mainly be attributed to an improper choice of the Z-R relationship. Conceptual rainfall-runoff simulations show similar results using either catchment average radar or rain gauge data, although the largest discharge peak observed, is seriously underestimated when applying radar data. Overall, for hydrological applications corrected weather radar information in a hilly environment can be used up to 70 km during a winter half-year.

  15. Vertical Variability of Radar Reflectivity and its Impact on Radar Rainfall Estimation

    NASA Astrophysics Data System (ADS)

    Mazari, N.; Sharif, H. O.; Xie, H.; Zeitler, J. W.

    2011-12-01

    Micro Rain Radar 2 (MRR-2) rainfall estimates were compared against rain observations from a tipping bucket rain gauge, and MRR-2 reflectivity measurements were compared to the Next Generation Weather Radar (NEXRAD) Level II reflectivity product. Three different storm events were selected for the comparison: 14-15 January, 2010 (lasted approx. 27 hours); 2-3 February, 2010 (lasted approx.19 hours); and 20 March, 2010 (lasted less than two hours). The MRR results show that the second gate (70 m above antenna) cumulative rainfall at one-minute intervals had the best agreement with the gauge cumulative rainfall observations, with an ρ = 0.94. Overall, both the MRR-2 rain rate (RR) and the rain rate derived from the Z-R relationship (Rz) underestimated rainfall at the one-minute and hourly intervals. The MRR-2 RR increased with height while Rz decreased significantly. In comparing reflectivity, the MRR agreed well with NEXRAD Level II reflectivity ( ρ = 0.71) for the gate centered at 980 m elevation above ground level. While the comparison between MRR and NEXRAD yielded lower agreement between the two sensors, best correlation between the MRR Rz and NEXRAD Rz was for the gate centered at 875 meters above ground (ρ = 0.42).

  16. Radar Rainfall Estimation with an X-Band Polarimetric Radar on Wheels: Early Results

    NASA Astrophysics Data System (ADS)

    Anagnostou, E. N.; Krajewski, W. F.; Anagnostou, M. N.; Kruger, A.; Miriovsky, B.

    2002-05-01

    The main goal of the X-Band Polarimetric Radar on Wheels (XPOW) study is aimed at exploring the advantages of dual-polarized X-band radar systems in radar rainfall estimation. Secondary goals include characterizing the reflectivity variability captured by National Weather Service WSR-88Ds and comparing different types of disdrometers. This investigation was facilitated through field experiments during which high-resolution polarimetric radar data from the National Observatory of Athens (NOA) mobile dual-polarization X-band radar were collected over well-instrumented sites. The XPOW field experiment was conducted in Iowa City, Iowa during October and November 2001. For this experiment, five disdrometers, a vertically pointing Doppler radar, and several dual-gauge tipping bucket rain gauge platforms were deployed in an area about 1.0 km by 1.5 km. These instruments were used to both augment and validate the data collected by the polarimetric radar, which was located approximately 8 km away. In the same area we collected data from some 14 rain gauges located within a high density cluster at the Iowa City Municipal Airport. The five disdrometers included two-dimensional video disdrometer, two optical disdrometers, an impact disdrometer, and a bistatic radar based disdrometer. The area in which these instruments were deployed corresponds to the size of one pixel from the Davenport, IA WSR-88D, located 80 km east of Iowa City, allowing exploration of the variability of reflectivity at scales smaller than a typical radar pixel. We will be presenting quantitative comparisons of rain rates and precipitation microphysical variables retrieved from XPOW and measured by the high-density network of gages and disdrometers. Furthermore, XPOW attenuation correction results will be compared to the un-attenuated WSR-88D reflectivity measurements providing a framework for assessing the deployed algorithm's microphysical retrievals.

  17. Real-time estimation of mean field bias in radar rainfall data

    NASA Astrophysics Data System (ADS)

    Seo, D.-J.; Breidenbach, J. P.; Johnson, E. R.

    1999-10-01

    To reduce systematic errors in radar rainfall data used for operational hydrologic forecasting, the precipitation estimation stream in the National Weather Service (NWS) uses procedures that estimate mean field bias in real time. Being a multiplicative correction over a very large area, bias adjustment has a huge impact, particularly on volumetric estimation of rainwater, and hence performance of the procedure is extremely important to quantitative hydrologic forecasting using radar rainfall data. In this paper, we describe a new procedure for real-time estimation of mean field bias in WSR-88D (Weather Surveillance Radar—1988 Doppler version) rainfall products. Based largely on operational experience of the existing procedures in NWS, the proposed procedure is intended to be unbiased, parsimonious, and intuitive. To evaluate the procedure, true validation is performed using hourly rain gage and WSR-88D rainfall data from Tulsa and Twin Lakes, Oklahoma.

  18. Digital signal processing of data from conventional weather radar: The DISPLACE method

    NASA Astrophysics Data System (ADS)

    Terblanche, Deon Etienne

    1997-09-01

    This thesis describes the development, testing and implementation of a new method to process the output from a weather radar's logarithmic receiver. The processing method, called DISPLACE, has proven to have many applications, and is computationally efficient and accurate. Its applications include the processing of digitized logarithmic receiver output in order to simulate different receiver transfer functions, the processing of multi-parameter radar measurements and the filtering of ground clutter. It facilitates the computation of CAPPI's and radar-rainfall accumulation. The thesis also deals with the upgrading of South African weather radars since about 1990 through the in-house developed radar data acquisition system and the procedures established to ensure accurate calibrations. In addition, the hydrometeorological infrastructure deployed in the Bethlehem research are is used in an integrated manner to verify data obtained using the new method. This work is well timed to address the needs that are now emerging in South Africa and clearly illustrate the role the NPRP played in reviving radar meteorology. The DISPLACE method is proving once again that the potential of conventional weather radar has not been fully exploited. It has also stimulated the interest of young technicians and scientists in the field of radar meteorology. This augurs well for the future use of weather radar in South Africa, both in the field of rainfall stimulation and as an integral part of systems designed to forecast and to help manage the effects of severe weather conditions.

  19. On the study of radar backscattering of ocean surface in response to rainfall

    NASA Astrophysics Data System (ADS)

    Liu, Xinan; Zheng, Quanan; Liu, Ren; Duncan, James H.

    2013-11-01

    A model of radar backscattering from the ocean surface in response to rainfall is developed. The model shows that the radar return intensity is a function of the wavelength and incident angle of the radar waves and the rain rate. The model explains the differences between the radar response to rain rate simultaneously observed by C-band ASAR and ground-based weather radar. An experiment on the simultaneous measurements of the characteristics of the ocean surface in response to rainfall and its radar back-scatter is performed in the laboratory. The experiment is carried out in a water pool that is 1.22 m by 1.22 m with a water depth of 0.3 m. Artificial rainfall is generated from an array of hypodermic needles. The surface characteristics including crowns, stalks and ring waves are measured with a cinematic Laser-Induced-Florescence (LIF) technique while secondary droplets are measured with a shadowgraph technique. The radar backscattering signal is recorded with a dual-polarized, ultra-wide band radar. The frequency dependence and polarization of the radar signatures due to the surface features are discussed. The work is supported by National Science Foundations, Division of Ocean Science.

  20. 14 CFR 121.357 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Airborne weather radar equipment... § 121.357 Airborne weather radar equipment requirements. (a) No person may operate any transport... December 31, 1964, unless approved airborne weather radar equipment has been installed in the airplane....

  1. 14 CFR 121.357 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Airborne weather radar equipment... § 121.357 Airborne weather radar equipment requirements. (a) No person may operate any transport... December 31, 1964, unless approved airborne weather radar equipment has been installed in the airplane....

  2. 14 CFR 121.357 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Airborne weather radar equipment... § 121.357 Airborne weather radar equipment requirements. (a) No person may operate any transport... December 31, 1964, unless approved airborne weather radar equipment has been installed in the airplane....

  3. 14 CFR 121.357 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Airborne weather radar equipment... § 121.357 Airborne weather radar equipment requirements. (a) No person may operate any transport... December 31, 1964, unless approved airborne weather radar equipment has been installed in the airplane....

  4. 14 CFR 121.357 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Airborne weather radar equipment... § 121.357 Airborne weather radar equipment requirements. (a) No person may operate any transport... December 31, 1964, unless approved airborne weather radar equipment has been installed in the airplane....

  5. Comparison of radar and raingauge measurements during heavy rainfall.

    PubMed

    Einfalt, T; Jessen, M; Mehlig, B

    2005-01-01

    Five heavy small-scale rainfall events in North Rhine-Westphalia (Germany) were investigated with radar and raingauge data. Special attention was paid to quality check and adjustment of radar data. Attenuation effects could be observed on both, C-Band and on X-Band radar. Adjustment of radar data to raingauge values turned out to be very difficult in the vicinity of heavy local rain cells. For the five affected regions the precipitation was quantified in the form of areal time series and cumulated radar images. As further result of this project, the spatial extent of the precipitation fields was identified and compared with radar and raingauge data. PMID:15790244

  6. Developments in radar and remote-sensing methods for measuring and forecasting rainfall.

    PubMed

    Collier, C G

    2002-07-15

    Over the last 25 years or so, weather-radar networks have become an integral part of operational meteorological observing systems. While measurements of rainfall made using radar systems have been used qualitatively by weather forecasters, and by some operational hydrologists, acceptance has been limited as a consequence of uncertainties in the quality of the data. Nevertheless, new algorithms for improving the accuracy of radar measurements of rainfall have been developed, including the potential to calibrate radars using the measurements of attenuation on microwave telecommunications links. Likewise, ways of assimilating these data into both meteorological and hydrological models are being developed. In this paper we review the current accuracy of radar estimates of rainfall, pointing out those approaches to the improvement of accuracy which are likely to be most successful operationally. Comment is made on the usefulness of satellite data for estimating rainfall in a flood-forecasting context. Finally, problems in coping with the error characteristics of all these data using both simple schemes and more complex four-dimensional variational analysis are being addressed, and are discussed briefly in this paper. PMID:12804253

  7. Application of radar rainfall estimates for surveillance of Aedes taeniorhynchus larvae.

    PubMed

    Ritchie, S A

    1993-06-01

    A preliminary investigation of land-based radar rainfall estimates for surveillance of Aedes taeniorhynchus larvae was conducted from January 1 to May 21, 1991 in Collier County, FL. Rainfall estimates from the National Weather Service RADAP II radar system, supplemented with tide gauge data, served as criteria for larval inspection. Rain, rain+tide and tide, respectively, triggered 48, 26 and 26% of the 14 proposed inspection trips. This system detected 7/8 larval broods found by Collier Mosquito Control District surveillance; the only brood not detected consisted of stragglers from an earlier brood exposed to cool weather and methoprene. A QUICKBASIC program that extracts Cartesian coordinates and rainfall estimates from RADAP II B-SCAN data was developed. PMID:8350081

  8. Uncertainty Analysis of Radar and Gauge Rainfall Estimates in the Russian River Basin

    NASA Astrophysics Data System (ADS)

    Cifelli, R.; Chen, H.; Willie, D.; Reynolds, D.; Campbell, C.; Sukovich, E.

    2013-12-01

    Radar Quantitative Precipitation Estimation (QPE) has been a very important application of weather radar since it was introduced and made widely available after World War II. Although great progress has been made over the last two decades, it is still a challenging process especially in regions of complex terrain such as the western U.S. It is also extremely difficult to make direct use of radar precipitation data in quantitative hydrologic forecasting models. To improve the understanding of rainfall estimation and distributions in the NOAA Hydrometeorology Testbed in northern California (HMT-West), extensive evaluation of radar and gauge QPE products has been performed using a set of independent rain gauge data. This study focuses on the rainfall evaluation in the Russian River Basin. The statistical properties of the different gridded QPE products will be compared quantitatively. The main emphasis of this study will be on the analysis of uncertainties of the radar and gauge rainfall products that are subject to various sources of error. The spatial variation analysis of the radar estimates is performed by measuring the statistical distribution of the radar base data such as reflectivity and by the comparison with a rain gauge cluster. The application of mean field bias values to the radar rainfall data will also be described. The uncertainty analysis of the gauge rainfall will be focused on the comparison of traditional kriging and conditional bias penalized kriging (Seo 2012) methods. This comparison is performed with the retrospective Multisensor Precipitation Estimator (MPE) system installed at the NOAA Earth System Research Laboratory. The independent gauge set will again be used as the verification tool for the newly generated rainfall products.

  9. Time-dependent Z-R relationships for estimating rainfall fields from radar measurements

    NASA Astrophysics Data System (ADS)

    Alfieri, L.; Claps, P.; Laio, F.

    2010-01-01

    The operational use of weather radars has become a widespread and useful tool for estimating rainfall fields. The radar-gauge adjustment is a commonly adopted technique which allows one to reduce bias and dispersion between radar rainfall estimates and the corresponding ground measurements provided by rain gauges. This paper investigates a new methodology for estimating radar-based rainfall fields by recalibrating at each time step the reflectivity-rainfall rate (Z-R) relationship on the basis of ground measurements provided by a rain gauge network. The power-law equation for converting reflectivity measurements into rainfall rates is readjusted at each time step, by calibrating its parameters using hourly Z-R pairs collected in the proximity of the considered time step. Calibration windows with duration between 1 and 24 h are used for estimating the parameters of the Z-R relationship. A case study pertaining to 19 rainfall events occurred in the north-western Italy is considered, in an area located within 25 km from the radar site, with available measurements of rainfall rate at the ground and radar reflectivity aloft. Results obtained with the proposed method are compared to those of three other literature methods. Applications are described for a posteriori evaluation of rainfall fields and for real-time estimation. Results suggest that the use of a calibration window of 2-5 h yields the best performances, with improvements that reach the 28% of the standard error obtained by using the most accurate fixed (climatological) Z-R relationship.

  10. wradlib - An Open Source Library for Weather Radar Data Processing

    NASA Astrophysics Data System (ADS)

    Heistermann, M.; Pfaff, Th.; Jacobi, S.

    2012-04-01

    Weather radar data is potentially useful in meteorology, hydrology, disaster prevention and mitigation. Its ability to provide information on precipitation with high spatial and temporal resolution over large areas makes it an invaluable tool for short term weather forecasting or flash flood forecasting. The indirect method of measuring the precipitation field, however, leads to a significant number of data artifacts, which usually must be removed or dealt with before the data can be used with acceptable quality. Data processing requires e.g. the transformation of measurements from polar to cartesian coordinates and from reflectivity to rainfall intensity, the composition of data from several radar sites in a common grid, clutter identification and removal, attenuation and VPR corrections, gauge adjustment and visualization. The complexity of these processing steps is a major obstacle for many potential users in science and practice. Adequate tools are available either only at significant costs with no access to the uncerlying source code, or they are incomplete, insufficiently documented and intransparent. The wradlib project has been initiated in order to lower the barrier for potential users of weather radar data in the geosciences and to provide a common platform for research on new algorithms. wradlib is an open source library for the full range of weather radar related processing algorithms, which is well documented and easy to use. The main parts of the library are currently implemented in the python programming language. Python is well known both for its ease of use as well as its ability to integrate code written in other programming languages like Fortran or C/C++. The well established Numpy and Scipy packages are used to provide decent performance for pure Python implementations of algorithms. We welcome contributions written in any computer language and will try to make them accessible from Python. We would like to present the current state of this

  11. Rainfall Measurement with a Ground Based Dual Frequency Radar

    NASA Technical Reports Server (NTRS)

    Takahashi, Nobuhiro; Horie, Hiroaki; Meneghini, Robert

    1997-01-01

    Dual frequency methods are one of the most useful ways to estimate precise rainfall rates. However, there are some difficulties in applying this method to ground based radars because of the existence of a blind zone and possible error in the radar calibration. Because of these problems, supplemental observations such as rain gauges or satellite link estimates of path integrated attenuation (PIA) are needed. This study shows how to estimate rainfall rate with a ground based dual frequency radar with rain gauge and satellite link data. Applications of this method to stratiform rainfall is also shown. This method is compared with single wavelength method. Data were obtained from a dual frequency (10 GHz and 35 GHz) multiparameter radar radiometer built by the Communications Research Laboratory (CRL), Japan, and located at NASA/GSFC during the spring of 1997. Optical rain gauge (ORG) data and broadcasting satellite signal data near the radar t location were also utilized for the calculation.

  12. Case study of heavy rainfall using Yong-In Testbed (YIT) dual-pol. radar in Korea

    NASA Astrophysics Data System (ADS)

    Lee, H. M.; Suk, M. K.; Nam, K. Y.; Hwang, J. Y.; Kim, H. L.; Yoon, J. S.; Ko, J. S.

    2015-12-01

    Weather Radar Center (WRC) in Korea Meteorological Administration (KMA) installed the Yong-In Testbed radar to examine the dual-pol. radar (S-band) variables and to develop the algorithms for applying to the operational dual-pol. radar network on August 2014. And it established the verification site at Jincheon located 28 km distance from YIT radar for the investigation of dual-pol. radar data and products on March 2014. There are the instruments of 2DVD (2-Dimensional Video Disdrometer), PARSIVEL (the laser-optical Particle Size Velocity), the tipping-bucket raingauges and the weighting raingauges at the verification site. This study analyses the heavy rainfall case such as typhoon, Chang-ma front from 2014 to 2015. WRC investigates the bias of the reflectivities (Z), differential reflectivities (ZDR) and computes the hydrometeor classification and the radar rainfall estimation. And WRC also calculate Korean equations R(Z, ZDR) for the radar rainfall estimation using 2DVD data and verifies the accuracy of the rainfall estimation for the heavy rainfall cases. We will investigate the characteristics of Korean rainfall system by using YIT radar continuously.

  13. Radar Rainfall Estimation using a Quadratic Z-R equation

    NASA Astrophysics Data System (ADS)

    Hall, Will; Rico-Ramirez, Miguel Angel; Kramer, Stefan

    2016-04-01

    The aim of this work is to test a method that enables the input of event based drop size distributions to alter a quadratic reflectivity (Z) to rainfall (R) equation that is limited by fixed upper and lower points. Results will be compared to the Marshall-Palmer Z-R relation outputs and validated by a network of gauges and a single polarisation weather radar located close to Essen, Germany. The time window over which the drop size distribution measurements will be collected is varied to note any effect on the generated quadratic Z-R relation. The new quadratic algorithm shows some distinct improvement over the Marshall-Palmer relationship through multiple events. The inclusion of a minimum number of Z-R points helped to decrease the associated error by defaulting back to the Marshall-Palmer equation if the limit was not reached. More research will be done to discover why the quadratic performs poorly in some events as there appears to be little correlation between number of drops or mean rainfall amount and the associated error. In some cases it seems the spatial distribution of the disdrometers has a significant effect as a large percentage of the rain bands pass to the north of two of the three disdrometers, frequently in a slightly north-easterly direction. However during widespread precipitation events the new algorithm works very well with reductions compared to the Marshall-Palmer relation.

  14. Influences of temporal rainfall radar and spatial rainfall-runoff model resolution on flood prediction

    NASA Astrophysics Data System (ADS)

    Weiler, Markus; Steinbrich, Andreas

    2013-04-01

    The rainfall-runoff-model DROGen (Distributed RunOff Generation) was developed to simulate runoff generation processes during floods and flash floods generation with a very high spatial resolution for the whole state of Baden-Württemberg in Southwest Germany. The model connects available spatial geo information with detailed process understanding at the plot and hillslope scale and is not calibrated. The model was successfully validated in 8 meso-scale watersheds with different geology, soils, topography and land-use and the results were very satisfying. We believe that the high spatial resolution of 1*1m² and a temporal resolution of 1 hour especially improved flow dynamics and the runoff concentration behaviour of the different runoff components. Some spatial information used by DROGen is available in very high resolution of 1*1m² (e.g. DEM and degree of sealing of land surface). Other data are much more generalized (e.g. soil information at the scale of 1:200.000) or at a fixed temporal resolution of one hour (e.g. calibrated precipitation radar data of the German weather survey (RADOLAN)). In order to find the adequate temporal and spatial resolution we investigated how the the spatial resolution of the geo data and the temporal resolution of the rainfall radar data effects the model result. Regarding the spatial resolution, we found, that the processes of runoff generation and runoff concentration are sensitive at different spatial scales. A decrease of spatial resolution from 1m to 25m lead to an implausible increase of the generation of saturation overland flow and to an accelerated concentration of subsurface flow, while Hortonian overland flow was almost not affected by the spatial resolution. For the model validation runs we realized that for short convective rain events a one hour resolution of the rainfall data might be not sufficient because of severe underestimation of peak intensities. We developed and tested a new method to estimate the temporal

  15. Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

    NASA Astrophysics Data System (ADS)

    Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

    2016-04-01

    Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

  16. Radar rainfall estimation in the context of post-event analysis of flash-flood events

    NASA Astrophysics Data System (ADS)

    Delrieu, G.; Bouilloud, L.; Boudevillain, B.; Kirstetter, P.-E.; Borga, M.

    2009-09-01

    Meteorology and Climatology, in press. Dinku, T., E.N. Anagnostou, and M. Borga, 2002: Improving Radar-Based Estimation of Rainfall over Complex Terrain. J. Appl. Meteor., 41, 1163-1178. Pellarin, T., G. Delrieu, G. M. Saulnier, H. Andrieu, B. Vignal, and J. D. Creutin, 2002: Hydrologic visibility of weather radar systems operating in mountainous regions: Case study for the Ardeche Catchment (France). Journal of Hydrometeorology, 3, 539-555.

  17. Simulation of radar rainfall errors and their propagation into rainfall-runoff processes

    NASA Astrophysics Data System (ADS)

    Aghakouchak, A.; Habib, E.

    2008-05-01

    Radar rainfall data compared with rain gauge measurements provide higher spatial and temporal resolution. However, radar data obtained form reflectivity patterns are subject to various errors such as errors in Z-R relationship, vertical profile of reflectivity, spatial and temporal sampling, etc. Characterization of such uncertainties in radar data and their effects on hydrologic simulations (e.g., streamflow estimation) is a challenging issue. This study aims to analyze radar rainfall error characteristics empirically to gain information on prosperities of random error representativeness and its temporal and spatial dependency. To empirically analyze error characteristics, high resolution and accurate rain gauge measurements are required. The Goodwin Creek watershed located in the north part of Mississippi is selected for this study due to availability of a dense rain gauge network. A total of 30 rain gauge measurement stations within Goodwin Creak watershed and the NWS Level II radar reflectivity data obtained from the WSR-88dD Memphis radar station with temporal resolution of 5min and spatial resolution of 1 km2 are used in this study. Radar data and rain gauge measurements comparisons are used to estimate overall bias, and statistical characteristics and spatio-temporal dependency of radar rainfall error fields. This information is then used to simulate realizations of radar error patterns with multiple correlated variables using Monte Calro method and the Cholesky decomposition. The generated error fields are then imposed on radar rainfall fields to obtain statistical realizations of input rainfall fields. Each simulated realization is then fed as input to a distributed physically based hydrological model resulting in an ensemble of predicted runoff hydrographs. The study analyzes the propagation of radar errors on the simulation of different rainfall-runoff processes such as streamflow, soil moisture, infiltration, and over-land flooding.

  18. Sensitivity Studies of the Radar-Rainfall Error Models

    NASA Astrophysics Data System (ADS)

    Villarini, G.; Krajewski, W. F.; Ciach, G. J.

    2007-12-01

    It is well acknowledged that there are large uncertainties associated with the operational quantitative precipitation estimates produced by the U.S. national network of WSR-88D radars. These errors are due to the measurement principles, parameter estimation, and not fully understood physical processes. Comprehensive quantitative evaluation of these uncertainties is still at an early stage. The authors proposed an empirically-based model in which the relation between true rainfall (RA) and radar-rainfall (RR) could be described as the product of a deterministic distortion function and a random component. However, how different values of the parameters in the radar-rainfall algorithms used to create these products impact the model results still remains an open question. In this study, the authors investigate the effects of different exponents in the Z-R relation (Marshall- Palmer, NEXRAD, and tropical) and of an anomalous propagation (AP) removal algorithm. Additionally, they generalize the model to describe the radar-rainfall uncertainties in the additive form. This approach is fully empirically based and rain gauge estimates are considered as an approximation of the true rainfall. The proposed results are based on a large sample (six years) of data from the Oklahoma City radar (KTLX) and processed through the Hydro-NEXRAD software system. The radar data are complemented with the corresponding rain gauge observations from the Oklahoma Mesonet, and the Agricultural Research Service Micronet.

  19. Use of weather radar for flood forecasting in the Sieve River Basin: A sensitivity analysis

    SciTech Connect

    Pessoa, M.L.; Bras, R.L.; Williams, E.R. )

    1993-03-01

    Weather radar, in combination with a distributed rainfall-runoff model, promises to significantly improve real-time flood forecasting. This paper investigates the value of radar-derived precipitation in forecasting streamflow in the Sieve River basin, near Florence, Italy. The basin is modeled with a distributed rainfall-runoff model that exploits topographic information available from digital elevation maps. The sensitivity of the flood forecast to various properties of the radar-derived rainfall is studied. It is found that use of the proper radar reflectivity-rainfall intensity (Z-R) relationship is the most crucial factor in obtaining correct flood hydrographs. Errors resulting from spatially averaging radar rainfall are acceptable, but the use of discrete point information (i.e. raingage) can lead to serious problems. Reducing the resolution of the 5-min radar signal by temporally averaging over 15 and 30 min does not lead to major errors. Using 3-bit radar data (rather than the usual 8-bit data) to represent intensities results in significant operational savings without serious problems in hydrograph accuracy. 24 refs., 28 figs., 2 tabs.

  20. Temporal interpolation of radar rainfall fields: meeting the stringent requirements of urban hydrological applications

    NASA Astrophysics Data System (ADS)

    Wang, Li-Pen; Ochoa-Rodriguez, Susana; Onof, Christian; Willems, Patrick

    2015-04-01

    Radar rainfall estimates are playing an increasingly important role in urban hydrological applications due to their better description of the spatial and temporal characteristics of rainfall. However, the operational radar rainfall products provided by national weather services (typically at 1 km / 5 min resolution) still fail to meet the stringent resolution requirements of urban hydrological applications. While the spatial and temporal resolution of rainfall inputs are strongly related, recent studies suggest that the latter generally constitutes a more critical factor and that temporal resolutions of ~1-2 min (i.e. below those currently available) are required for urban hydrological applications, while spatial resolutions of ~1 km (i.e. close to those currently available) appear to be sufficient. Traditional strategies for obtaining higher temporal resolution radar rainfall estimates include changes in radar scanning strategies and stochastic downscaling. However, the former is not always possible, due to hardware limitations, and the latter results in large ensembles members which hinder practical use. In this work a temporal interpolation method, based upon the multi-scale variational optical flow technique, is proposed to generate high temporal-resolution (i.e. 1-2 min) radar rainfall estimates. The proposed method has been successfully applied to obtain radar rainfall estimates at 1 and 2 min temporal resolutions from UK Met Office C-band radar products originally at 5 and 10 min temporal resolution and varying spatial resolutions of 1 km, 500 m and 100 m. The performance of the higher temporal-resolution radar rainfall estimates was assessed through comparison against local rain gauge records collected at a pilot urban catchment (size ~ 865 ha) in North-East London. A further evaluation was conducted by applying the different rainfall products as input to the hydraulic model of the pilot catchment and comparing the hydraulic outputs against available flow

  1. A radar backscattering mechanism of ocean surface in response to rainfall

    NASA Astrophysics Data System (ADS)

    Liu, Xinan; Zheng, Quanan; Liu, Ren; Duncan, James H.

    2012-11-01

    The characteristics of ocean surface in response to rainfall and its radar back-scatter are simultaneously measured in laboratory. The experiment is carried out in a water pool that is 1.22 m by 1.22 m with a water depth of 0.3 m. Artificial rainfall is generated from an array of hypodermic needles. The surface characteristics including crowns, stalks, secondary droplets and ring waves are measured with a cinematic Laser-Induced-Florescence (LIF) technique. Our experimental results show that impinging raindrops on the water surface generate various water surface structures with different relative sizes. Among them stalks and crowns comprise the dominant radar backscattering. On the basis of these laboratory experiments and theories of radar scattering from a rough surface, a near-resonance radar backscattering model for quantifying the dependence of the radar return intensity on rain rate on the ocean surface is developed. The model explains the radar response to rain rate simultaneously observed by C-band ASAR and ground-based weather radar. The physical model provides reasonable mechanisms to explain the frequency dependence and polarization behavior of radar signatures from rain cells on the ocean surface. This work is supported by the National Science Foundation, Division of Ocean Sciences under grant OCE962107.

  2. Statistical evaluation of a radar rainfall system for sewer system management

    NASA Astrophysics Data System (ADS)

    Vieux, B. E.; Vieux, J. E.

    2005-09-01

    Urban areas are faced with mounting demands for managing waste and stormwater for a cleaner environment. Rainfall information is a critical component in efficient management of urban drainage systems. A major water quality impact affecting receiving waterbodies is the discharge of untreated waste and stormwater during precipitation, termed wet weather flow. Elimination or reduction of wet weather flow in metropolitan sewer districts is a major goal of environmental protection agencies and often requires considerable capital improvements. Design of these improvements requires accurate rainfall data in conjunction with monitored wastewater flow data. Characterizing the hydrologic/hydraulic performance of the sewer using distant rain gauges can cause oversizing and wasted expenditures. Advanced technology has improved our ability to measure accurately rainfall over large areas. Weather radar, when combined with rain gauge measurements, provides detailed information concerning rainfall intensities over specific watersheds. Knowing how much rain fell over contributing areas during specific periods aids in characterizing inflow and infiltration to sanitary and combined sewers, calibration of sewer system models, and in operation of predictive real-time control measures. Described herein is the design of a system for managing rainfall information for sewer system management, along with statistical analysis of 60 events from a large metropolitan sewer district. Analysis of the lower quartile rainfall events indicates that the expected average difference is 25.61%. Upper quartile rainfall events have an expected average difference of 17.25%. Rain gauge and radar accumulations are compared and evaluated in relation to specific needs of an urban application. Overall, the events analyzed agree to within ± 8% based on the median average difference between gauge and radar.

  3. 14 CFR 125.223 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Airborne weather radar equipment... Equipment Requirements § 125.223 Airborne weather radar equipment requirements. (a) No person may operate an airplane governed by this part in passenger-carrying operations unless approved airborne weather...

  4. 14 CFR 125.223 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Airborne weather radar equipment... Equipment Requirements § 125.223 Airborne weather radar equipment requirements. (a) No person may operate an airplane governed by this part in passenger-carrying operations unless approved airborne weather...

  5. 14 CFR 125.223 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Airborne weather radar equipment... Equipment Requirements § 125.223 Airborne weather radar equipment requirements. (a) No person may operate an airplane governed by this part in passenger-carrying operations unless approved airborne weather...

  6. 14 CFR 125.223 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Airborne weather radar equipment... Equipment Requirements § 125.223 Airborne weather radar equipment requirements. (a) No person may operate an airplane governed by this part in passenger-carrying operations unless approved airborne weather...

  7. 14 CFR 125.223 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Airborne weather radar equipment... Equipment Requirements § 125.223 Airborne weather radar equipment requirements. (a) No person may operate an airplane governed by this part in passenger-carrying operations unless approved airborne weather...

  8. Storm Scale Rainfall Estimation and Quantifying Uncertainty from Ground-based Dual-Polarimetric Radar

    NASA Astrophysics Data System (ADS)

    Marks, D. A.; Wolff, D. B.

    2012-12-01

    Ground-based radar and gauge rainfall estimates will be vital components in both statistical and physical validation of Global Precipitation Measurement (GPM) constellation satellite rainfall retrievals, and the quantification of uncertainty of the ground-based measurements is a key requirement of the GPM Ground Validation (GV) program. Legacy Tropical Rainfall Measuring Mission (TRMM) GV radar reflectivity - rain rate (Z-R) lookup tables are determined by matching reflectivity and rain gauge distributions via the probability matching method (PMM) over a minimum time period of one month, thereby constraining the radar-derived accumulations to match the gauge accumulations. However, the usage of climatological PMM tables for rain rate estimation is not representative for the storm scale accumulations relevant to GPM science hydrology applications. The availability of S-band dual-polarimetric data from the KPOL radar at Kwajalein Atoll, RMI and KMLB (WSR-88D) radar at Melbourne, FL provides opportunity to evaluate alternative rainfall estimation methods with error quantification derived via comparison with independent rain gauges. In this study, statistical comparisons of rainfall accumulation from legacy PMM and two multi-parameter methods are evaluated on a GPM relevant storm scale (~3 hours). The first multi-parameter approach considers rain rate equations derived from several years of Joss-Waldvogel disdrometer data near both radars (JW method), while the second involves a polarimetrically-based Z-R relation with a continuously adjusted coefficient tuned to the evolving drop size distribution (Bringi method). The primary objective is to generate rainfall accumulations and associated error estimates with fidelity at a storm scale relevant to GPM goals. Of further interest will be the difference in results between the two regimes; the KPOL environment being a tropical oceanic climate, while the KMLB environment is influenced by continental, coastal, and maritime

  9. SUBPIXEL-SCALE RAINFALL VARIABILITY AND THE EFFECTS ON SEPARATION OF RADAR AND GAUGE RAINFALL ERRORS

    EPA Science Inventory

    One of the primary sources of the discrepancies between radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that the respective data sets are meant to represent. ...

  10. An Empirically Based Error-Model for Radar Rainfall Estimates

    NASA Astrophysics Data System (ADS)

    Ciach, G. J.

    2004-05-01

    Mathematical modeling of the way radar rainfall (RR) approximates the physical truth is a prospective method to quantify the RR uncertainties. In this approach one can represent RR in the form of an "observation equation," that is, as a function of the corresponding true rainfall and a random error process. The error process describes the cumulative effect of all the sources of RR uncertainties. We present the results of our work on the identification and estimation of this relationship. They are based on the Level II reflectivity data from the WSR-88D radar in Tulsa, Oklahoma, and rainfall measurements from 23 surrounding Oklahoma Mesonet raingauges. Accumulation intervals from one hour to one day were analyzed using this sample. The raingauge accumulations were used as an approximation of the true rainfall in this study. The RR error-model that we explored is factorized into a deterministic distortion, which is a function of the true rainfall, and a multiplicative random error factor that is a positively-defined random variable. The distribution of the error factor depends on the true rainfall, however, its expectation in this representation is always equal to one (all the biases are modeled by the deterministic component). With this constraint, the deterministic distortion function can be defined as the conditional mean of RR conditioned on the true rainfall. We use nonparametric regression to estimate the deterministic distortion, and the variance and quantiles of the random error factor, as functions of the true rainfall. The results show that the deterministic distortion is a nonlinear function of the true rainfall that indicates systematic overestimation of week rainfall and underestimation of strong rainfall (conditional bias). The standard deviation of the error factor is a decreasing function of the true rainfall that ranges from about 0.8 for week rainfall to about 0.3 for strong rainfall. For larger time-scales, both the deterministic distortion and the

  11. Multi-scale evaluation of the IFloodS radar-rainfall products

    NASA Astrophysics Data System (ADS)

    Seo, Bong-Chul; Krajewski, Witold; Cunha, Luciana; Dolan, Brenda; Smith, James; Rutledge, Steven; Petersen, Walter

    2014-05-01

    Rainfall products estimated using ground-based radars are often used as reference to assess capabilities and limitations of using satellite rainfall estimates in hydrologic modeling and prediction. During the spring of 2013, NASA conducted a hydrology-oriented field campaign called Iowa Flood Studies (IFloodS) in the central and northeastern Iowa in the United States, as a part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission. The purpose of IFloodS was to enhance the understanding of flood-related rainfall processes and the predictability in flood forecasting. While there are multiple types of rainfall data sets (e.g., satellite, radar, rain gauge, and disdrometer) available as the observational assets of IFloodS, the authors focus on the evaluation of multi-scale rainfall products observed from ground-based radars. The radar-only products used in the evaluation are the NEXRAD single polarization products (i.e., Stage IV, NMQ Q2, and Iowa Flood Center rainfall maps) and products generated using dual-polarization procedures (i.e., the U.S. National Weather Service operational and Colorado State University experimental blended precipitation processing algorithms) with comparable space and time resolution. The NASA NPOL S-band radar products are also evaluated and compared with the aforementioned NEXRAD products. The uncertainty for different temporal and spatial resolution products is characterized using ground reference data of dense rain gauge and disdrometer networks. This multi-scale characterization is required for hydrologic modeling frameworks that assess model predictive abilities as a function of space and time scales.

  12. Radar-based rainfall estimation: Improving Z/R relations through comparison of drop size distributions, rainfall rates and radar reflectivity patterns

    NASA Astrophysics Data System (ADS)

    Neuper, Malte; Ehret, Uwe

    2014-05-01

    The relation between the measured radar reflectivity factor Z and surface rainfall intensity R - the Z/R relation - is profoundly complex, so that in general one speaks about radar-based quantitative precipitation estimation (QPE) rather than exact measurement. Like in Plato's Allegory of the Cave, what we observe in the end is only the 'shadow' of the true rainfall field through a very small backscatter of an electromagnetic signal emitted by the radar, which we hope has been actually reflected by hydrometeors. The meteorological relevant and valuable Information is gained only indirectly by more or less justified assumptions. One of these assumptions concerns the drop size distribution, through which the rain intensity is finally associated with the measured radar reflectivity factor Z. The real drop size distribution is however subject to large spatial and temporal variability, and consequently so is the true Z/R relation. Better knowledge of the true spatio-temporal Z/R structure therefore has the potential to improve radar-based QPE compared to the common practice of applying a single or a few standard Z/R relations. To this end, we use observations from six laser-optic disdrometers, two vertically pointing micro rain radars, 205 rain gauges, one rawindsonde station and two C-band Doppler radars installed or operated in and near the Attert catchment (Luxembourg). The C-band radars and the rawindsonde station are operated by the Belgian and German Weather Services, the rain gauge data was partly provided by the French, Dutch, Belgian, German Weather Services and the Ministry of Agriculture of Luxembourg and the other equipment was installed as part of the interdisciplinary DFG research project CAOS (Catchment as Organized Systems). With the various data sets correlation analyzes were executed. In order to get a notion on the different appearance of the reflectivity patterns in the radar image, first of all various simple distribution indices (for example the

  13. Propagation of radar rainfall uncertainty in urban flood simulations

    NASA Astrophysics Data System (ADS)

    Liguori, Sara; Rico-Ramirez, Miguel

    2013-04-01

    This work discusses the results of the implementation of a novel probabilistic system designed to improve ensemble sewer flow predictions for the drainage network of a small urban area in the North of England. The probabilistic system has been developed to model the uncertainty associated to radar rainfall estimates and propagate it through radar-based ensemble sewer flow predictions. The assessment of this system aims at outlining the benefits of addressing the uncertainty associated to radar rainfall estimates in a probabilistic framework, to be potentially implemented in the real-time management of the sewer network in the study area. Radar rainfall estimates are affected by uncertainty due to various factors [1-3] and quality control and correction techniques have been developed in order to improve their accuracy. However, the hydrological use of radar rainfall estimates and forecasts remains challenging. A significant effort has been devoted by the international research community to the assessment of the uncertainty propagation through probabilistic hydro-meteorological forecast systems [4-5], and various approaches have been implemented for the purpose of characterizing the uncertainty in radar rainfall estimates and forecasts [6-11]. A radar-based ensemble stochastic approach, similar to the one implemented for use in the Southern-Alps by the REAL system [6], has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A

  14. Weather models as virtual sensors to data-driven rainfall predictions in urban watersheds

    NASA Astrophysics Data System (ADS)

    Cozzi, Lorenzo; Galelli, Stefano; Pascal, Samuel Jolivet De Marc; Castelletti, Andrea

    2013-04-01

    Weather and climate predictions are a key element of urban hydrology where they are used to inform water management and assist in flood warning delivering. Indeed, the modelling of the very fast dynamics of urbanized catchments can be substantially improved by the use of weather/rainfall predictions. For example, in Singapore Marina Reservoir catchment runoff processes have a very short time of concentration (roughly one hour) and observational data are thus nearly useless for runoff predictions and weather prediction are required. Unfortunately, radar nowcasting methods do not allow to carrying out long - term weather predictions, whereas numerical models are limited by their coarse spatial scale. Moreover, numerical models are usually poorly reliable because of the fast motion and limited spatial extension of rainfall events. In this study we investigate the combined use of data-driven modelling techniques and weather variables observed/simulated with a numerical model as a way to improve rainfall prediction accuracy and lead time in the Singapore metropolitan area. To explore the feasibility of the approach, we use a Weather Research and Forecast (WRF) model as a virtual sensor network for the input variables (the states of the WRF model) to a machine learning rainfall prediction model. More precisely, we combine an input variable selection method and a non-parametric tree-based model to characterize the empirical relation between the rainfall measured at the catchment level and all possible weather input variables provided by WRF model. We explore different lead time to evaluate the model reliability for different long - term predictions, as well as different time lags to see how past information could improve results. Results show that the proposed approach allow a significant improvement of the prediction accuracy of the WRF model on the Singapore urban area.

  15. A New Method for Radar Rainfall Estimation Using Merged Radar and Gauge Derived Fields

    NASA Astrophysics Data System (ADS)

    Hasan, M. M.; Sharma, A.; Johnson, F.; Mariethoz, G.; Seed, A.

    2014-12-01

    Accurate estimation of rainfall is critical for any hydrological analysis. The advantage of radar rainfall measurements is their ability to cover large areas. However, the uncertainties in the parameters of the power law, that links reflectivity to rainfall intensity, have to date precluded the widespread use of radars for quantitative rainfall estimates for hydrological studies. There is therefore considerable interest in methods that can combine the strengths of radar and gauge measurements by merging the two data sources. In this work, we propose two new developments to advance this area of research. The first contribution is a non-parametric radar rainfall estimation method (NPZR) which is based on kernel density estimation. Instead of using a traditional Z-R relationship, the NPZR accounts for the uncertainty in the relationship between reflectivity and rainfall intensity. More importantly, this uncertainty can vary for different values of reflectivity. The NPZR method reduces the Mean Square Error (MSE) of the estimated rainfall by 16 % compared to a traditionally fitted Z-R relation. Rainfall estimates are improved at 90% of the gauge locations when the method is applied to the densely gauged Sydney Terrey Hills radar region. A copula based spatial interpolation method (SIR) is used to estimate rainfall from gauge observations at the radar pixel locations. The gauge-based SIR estimates have low uncertainty in areas with good gauge density, whilst the NPZR method provides more reliable rainfall estimates than the SIR method, particularly in the areas of low gauge density. The second contribution of the work is to merge the radar rainfall field with spatially interpolated gauge rainfall estimates. The two rainfall fields are combined using a temporally and spatially varying weighting scheme that can account for the strengths of each method. The weight for each time period at each location is calculated based on the expected estimation error of each method

  16. Precipitation thresholds and debris flow warning: comparing gauge versus weather radar detection

    NASA Astrophysics Data System (ADS)

    Marra, Francesco; Borga, Marco; Creutin, Jean-Dominique

    2013-04-01

    Methods relying on rainfall thresholds for debris-flow warning have a long tradition in geomorphology. Usually, the precipitation thresholds are developed based on rain gauge and debris flows data. However, it is well known that extreme rainfall sampling errors over rugged topography may lead to biased precipitation thresholds. At least two reasons contribute to such sampling errors: i) the regions of complex topography have low rain gauge densities; ii) orography may enhance intense precipitation at very localized places. We studied six storm events that triggered several debris flows each over the Trentino-Alto Adige Region, in the central Italian Alps, between 2005 and 2010. The region is monitored by i) a rain gauge network with an average density of 1/100 km2 and ii) a C-band radar instrument. Radar data have been accurately corrected for errors due to ground clutter contamination, beam blockages, vertical profile of reflectivity, attenuation and wet radome in order to obtain a high quality set of radar-based rainfall fields. We characterized the variability of each rainfall event using space (horizontal) and time variograms and we investigated the altitude (vertical) distribution of rainfall using hypsometric rainfall moments. We also defined the local severity of the rainfall accumulations over the debris flow areas for different time accumulations. We used the radar precipitation fields to represent space-time rainfall variability and we simulated gauge sampling with a stochastic model accounting for sub-grid variability of precipitation and for gauge measurement errors. We show that rain gauges systematically underestimate the local severity over the proven debris flow triggering locations. This leads to biased precipitation thresholds. In this respect gauge spatial sampling appears inappropriate both in the horizontal and in the vertical dimensions while the usual gauge time sampling looks appropriate. Moreover, this shows the potential of rainfall

  17. 14 CFR 135.175 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 14 Aeronautics and Space 3 2011-01-01 2011-01-01 false Airborne weather radar equipment... Aircraft and Equipment § 135.175 Airborne weather radar equipment requirements. (a) No person may operate a large, transport category aircraft in passenger-carrying operations unless approved airborne...

  18. 14 CFR 135.175 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 14 Aeronautics and Space 3 2010-01-01 2010-01-01 false Airborne weather radar equipment... Aircraft and Equipment § 135.175 Airborne weather radar equipment requirements. (a) No person may operate a large, transport category aircraft in passenger-carrying operations unless approved airborne...

  19. 14 CFR 135.175 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 14 Aeronautics and Space 3 2013-01-01 2013-01-01 false Airborne weather radar equipment... Aircraft and Equipment § 135.175 Airborne weather radar equipment requirements. (a) No person may operate a large, transport category aircraft in passenger-carrying operations unless approved airborne...

  20. 14 CFR 135.175 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 14 Aeronautics and Space 3 2012-01-01 2012-01-01 false Airborne weather radar equipment... Aircraft and Equipment § 135.175 Airborne weather radar equipment requirements. (a) No person may operate a large, transport category aircraft in passenger-carrying operations unless approved airborne...

  1. 14 CFR 135.175 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 14 Aeronautics and Space 3 2014-01-01 2014-01-01 false Airborne weather radar equipment... Aircraft and Equipment § 135.175 Airborne weather radar equipment requirements. (a) No person may operate a large, transport category aircraft in passenger-carrying operations unless approved airborne...

  2. Long-term accounting for raindrop size distribution variations improves quantitative precipitation estimation by weather radar

    NASA Astrophysics Data System (ADS)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2016-04-01

    Weather radars provide information on the characteristics of precipitation at high spatial and temporal resolution. Unfortunately, rainfall measurements by radar are affected by multiple error sources. The current study is focused on the impact of variations of the raindrop size distribution on radar rainfall estimates. Such variations lead to errors in the estimated rainfall intensity (R) and specific attenuation (k) when using fixed relations for the conversion of the observed reflectivity (Z) into R and k. For non-polarimetric radar, this error source has received relatively little attention compared to other error sources. We propose to link the parameters of the Z-R and Z-k relations directly to those of the normalized gamma DSD. The benefit of this procedure is that it reduces the number of unknown parameters. In this work, the DSD parameters are obtained using 1) surface observations from a Parsivel and Thies LPM disdrometer, and 2) a Monte Carlo optimization procedure using surface rain gauge observations. The impact of both approaches for a given precipitation type is assessed for 45 days of summertime precipitation observed in The Netherlands. Accounting for DSD variations using disdrometer observations leads to an improved radar QPE product as compared to applying climatological Z-R and Z-k relations. This especially holds for situations where widespread stratiform precipitation is observed. The best results are obtained when the DSD parameters are optimized. However, the optimized Z-R and Z-k relations show an unrealistic variability that arises from uncorrected error sources. As such, the optimization approach does not result in a realistic DSD shape but instead also accounts for uncorrected error sources resulting in the best radar rainfall adjustment. Therefore, to further improve the quality of preciptitation estimates by weather radar, usage should either be made of polarimetric radar or by extending the network of disdrometers.

  3. Simulation of Radar Rainfall Fields: A Random Error Model

    NASA Astrophysics Data System (ADS)

    Aghakouchak, A.; Habib, E.; Bardossy, A.

    2008-12-01

    Precipitation is a major input in hydrological and meteorological models. It is believed that uncertainties due to input data will propagate in modeling hydrologic processes. Stochastically generated rainfall data are used as input to hydrological and meteorological models to assess model uncertainties and climate variability in water resources systems. The superposition of random errors of different sources is one of the main factors in uncertainty of radar estimates. One way to express these uncertainties is to stochastically generate random error fields to impose them on radar measurements in order to obtain an ensemble of radar rainfall estimates. In the method introduced here, the random error consists of two components: purely random error and dependent error on the indicator variable. Model parameters of the error model are estimated using a heteroscedastic maximum likelihood model in order to account for variance heterogeneity in radar rainfall error estimates. When reflectivity values are considered, the exponent and multiplicative factor of the Z-R relationship are estimated simultaneously with the model parameters. The presented model performs better compared to the previous approaches that generally result in unaccounted heteroscedasticity in error fields and thus radar ensemble.

  4. An integrated approach for identifying homogeneous regions of extreme rainfall events and estimating IDF curves in Southern Ontario, Canada: Incorporating radar observations

    NASA Astrophysics Data System (ADS)

    Paixao, Edson; Mirza, M. Monirul Qader; Shephard, Mark W.; Auld, Heather; Klaassen, Joan; Smith, Graham

    2015-09-01

    Reliable extreme rainfall information is required for many applications including infrastructure design, management of water resources, and planning for weather-related emergencies in urban and rural areas. In this study, in situ TBRG sub-daily rainfall rate observations have been supplemented with weather radar information to better capture the spatial and temporal variability of heavy rainfall events regionally. Comparison of extreme rainfall events show that the absolute differences between the rain gauge and radar generally increase with increasing rainfall. Better agreement between the two observations is found when comparing the collocated radar and TBRG annual maximum values. The median difference is <18% for the annual maximum rainfall values ⩽50 mm. The median of difference of IDF estimates obtained through the Gumbel distribution for 10-year return period values computed from TBRG and radar are also found to be 4%. The overall results of this analysis demonstrates the potential value of incorporating remotely sensed radar with traditional point source TBRG network observations to provide additional insight on extreme rainfall events regionally, especially in terms of identifying homogeneous regions of extreme rainfall. The radar observations are particularly useful in areas where there is insufficient TBRG station density to statistically capture the extreme rainfall events.

  5. Simulation of radar reflectivity and surface measurements of rainfall

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Bringi, V. N.

    1987-01-01

    Raindrop size distributions (RSDs) are often estimated using surface raindrop sampling devices (e.g., disdrometers) or optical array (2D-PMS) probes. A number of authors have used these measured distributions to compute certain higher-order RSD moments that correspond to radar reflectivity, attenuation, optical extinction, etc. Scatter plots of these RSD moments versus disdrometer-measured rainrates are then used to deduce physical relationships between radar reflectivity, attenuation, etc., which are measured by independent instruments (e.g., radar), and rainrate. In this paper RSDs of the gamma form as well as radar reflectivity (via time series simulation) are simulated to study the correlation structure of radar estimates versus rainrate as opposed to RSD moment estimates versus rainrate. The parameters N0, D0 and m of a gamma distribution are varied over the range normally found in rainfall, as well as varying the device sampling volume. The simulations are used to explain some possible features related to discrepancies which can arise when radar rainfall measurements are compared with surface or aircraft-based sampling devices.

  6. Simulation of a weather radar display for over-water airborne radar approaches

    NASA Technical Reports Server (NTRS)

    Clary, G. R.

    1983-01-01

    Airborne radar approach (ARA) concepts are being investigated as a part of NASA's Rotorcraft All-Weather Operations Research Program on advanced guidance and navigation methods. This research is being conducted using both piloted simulations and flight test evaluations. For the piloted simulations, a mathematical model of the airborne radar was developed for over-water ARAs to offshore platforms. This simulated flight scenario requires radar simulation of point targets, such as oil rigs and ships, distributed sea clutter, and transponder beacon replies. Radar theory, weather radar characteristics, and empirical data derived from in-flight radar photographs are combined to model a civil weather/mapping radar typical of those used in offshore rotorcraft operations. The resulting radar simulation is realistic and provides the needed simulation capability for ongoing ARA research.

  7. Sensitivity of power functions to aggregation: Bias and uncertainty in radar rainfall retrieval

    NASA Astrophysics Data System (ADS)

    Sassi, M. G.; Leijnse, H.; Uijlenhoet, R.

    2014-10-01

    Rainfall retrieval using weather radar relies on power functions between radar reflectivity Z and rain rate R. The nonlinear nature of these relations complicates the comparison of rainfall estimates employing reflectivities measured at different scales. Transforming Z into R using relations that have been derived for other scales results in a bias and added uncertainty. We investigate the sensitivity of Z-R relations to spatial and temporal aggregation using high-resolution reflectivity fields for five rainfall events. Existing Z-R relations were employed to investigate the behavior of aggregated Z-R relations with scale, the aggregation bias, and the variability of the estimated rain rate. The prefactor and the exponent of aggregated Z-R relations systematically diverge with scale, showing a break that is event-dependent in the temporal domain and nearly constant in space. The systematic error associated with the aggregation bias at a given scale can become of the same order as the corresponding random error associated with intermittent sampling. The bias can be constrained by including information about the variability of Z within a certain scale of aggregation, and is largely captured by simple functions of the coefficient of variation of Z. Several descriptors of spatial and temporal variability of the reflectivity field are presented, to establish the links between variability descriptors and resulting aggregation bias. Prefactors in Z-R relations can be related to multifractal properties of the rainfall field. We find evidence of scaling breaks in the structural analysis of spatial rainfall with aggregation.

  8. Influence of small scale rainfall variability on standard comparison tools between radar and rain gauge data

    NASA Astrophysics Data System (ADS)

    Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Schellart, Alma; Berne, Alexis; Lovejoy, Shaun

    2014-03-01

    Rain gauges and weather radars do not measure rainfall at the same scale; roughly 20 cm for the former and 1 km for the latter. This significant scale gap is not taken into account by standard comparison tools (e.g. cumulative depth curves, normalized bias, RMSE) despite the fact that rainfall is recognized to exhibit extreme variability at all scales. In this paper we suggest to revisit the debate of the representativeness of point measurement by explicitly modelling small scale rainfall variability with the help of Universal Multifractals. First the downscaling process is validated with the help of a dense networks of 16 disdrometers (in Lausanne, Switzerland), and one of 16 rain gauges (Bradford, United Kingdom) both located within a 1 km2 area. Second this downscaling process is used to evaluate the impact of small scale (i.e. sub-radar pixel) rainfall variability on the standard indicators. This is done with rainfall data from the Seine-Saint-Denis County (France). Although not explaining all the observed differences, it appears that this impact is significant which suggests changing some usual practice.

  9. Comparison of rain gauge and radar data as input to an urban rainfall-runoff model.

    PubMed

    Quirmbach, M; Schultz, G A

    2002-01-01

    This paper presents an application of radar data (DX-product of the German Weather Service) with a high resolution in space (1 degree x 1 km) and time (delta t = 5 minutes) in urban hydrology. The radar data and data of rain gauges with different locations in the test catchment were compared concerning their suitability as input into an urban rainfall-runoff model. In order to evaluate the accuracy of model simulation results, five evaluation criteria have been specified which are relevant for an efficient management of sewer systems and wastewater treatment plants. The results demonstrate that radar data should be used in urban hydrology if distances > 4 km between rain gauge and catchment exist and for catchments with a density of rain gauges smaller than 1 rain gauge per 16 km2. PMID:11888180

  10. Sensitivity of Flow Uncertainty to Radar Rainfall Uncertainty in the Context of Operational Distributed Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Carpenter, T. M.; Georgakakos, K. P.; Georgakakos, K. P.

    2001-12-01

    The current study focuses on the sensitivity of distributed model flow forecast uncertainty to the uncertainty in the radar rainfall input. Various studies estimate a 30 to 100% uncertainty in radar rainfall estimates from the operational NEXRAD radars. This study addresses the following questions: How does this uncertainty in rainfall input impact the flow simulations produced by a hydrologic model? How does this effect compare to the uncertainty in flow forecasts resulting from initial condition and model parametric uncertainty? The hydrologic model used, HRCDHM, is a catchment-based, distributed hydrologic model and accepts hourly precipitation input from the operational WSR-88D weather radar. A GIS is used to process digital terrain data, delineate sub-catchments of a given large watershed, and supply sub-catchment characteristics (subbasin area, stream length, stream slope and channel-network topology) to the hydrologic model components. HRCDHM uses an adaptation of the U.S. NWS operational Sacramento soil moisture accounting model to produce runoff for each sub-catchment within the larger study watershed. Kinematic or Muskingum-Cunge channel routing is implemented to combine and route sub-catchment flows through the channel network. Available spatial soils information is used to vary hydrologic model parameters from sub-catchment to sub-catchment. HRCDHM was applied to the 2,500 km2 Illinois River watershed in Arkansas and Oklahoma with outlet at Tahlequah, Oklahoma. The watershed is under the coverage of the operational WSR-88D radar at Tulsa, Oklahoma. For distributed modeling, the watershed area has been subdivided into sub-catchments with an average area of 80km2. Flow simulations are validated at various gauged locations within the watershed. A Monte Carlo framework was used to assess the sensitivity of the simulated flows to uncertainty in radar input for different radar error distributions (uniform or exponential), and to make comparisons to the flow

  11. Evaluation of Various Radar Data Quality Control Algorithms Based on Accumulated Radar Rainfall Statistics

    NASA Technical Reports Server (NTRS)

    Robinson, Michael; Steiner, Matthias; Wolff, David B.; Ferrier, Brad S.; Kessinger, Cathy; Einaudi, Franco (Technical Monitor)

    2000-01-01

    The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. A fundamental and extremely important step in creating high-quality GV products is radar data quality control. Quality control (QC) processing of TRMM GV radar data is based on some automated procedures, but the current QC algorithm is not fully operational and requires significant human interaction to assure satisfactory results. Moreover, the TRMM GV QC algorithm, even with continuous manual tuning, still can not completely remove all types of spurious echoes. In an attempt to improve the current operational radar data QC procedures of the TRMM GV effort, an intercomparison of several QC algorithms has been conducted. This presentation will demonstrate how various radar data QC algorithms affect accumulated radar rainfall products. In all, six different QC algorithms will be applied to two months of WSR-88D radar data from Melbourne, Florida. Daily, five-day, and monthly accumulated radar rainfall maps will be produced for each quality-controlled data set. The QC algorithms will be evaluated and compared based on their ability to remove spurious echoes without removing significant precipitation. Strengths and weaknesses of each algorithm will be assessed based on, their abilit to mitigate both erroneous additions and reductions in rainfall accumulation from spurious echo contamination and true precipitation removal, respectively. Contamination from individual spurious echo categories will be quantified to further diagnose the abilities of each radar QC algorithm. Finally, a cost-benefit analysis will be conducted to determine if a more automated QC algorithm is a viable alternative to the current, labor-intensive QC algorithm employed by TRMM GV.

  12. Simulation of operational typhoon rainfall nowcasting using radar reflectivity combined with meteorological data

    NASA Astrophysics Data System (ADS)

    Wei, Chih-Chiang

    2014-06-01

    In this study, a practical typhoon effective rainfall nowcasting (TERN) model was developed for use in real-time forecasting. The TERN model was derived from a data-driven adaptive network-based fuzzy inference system (ANFIS). The model inputs include meteorological data and radar reflectivity data. The model simulation process begins with an online typhoon warning issued by the Central Weather Bureau (CWB) of Taiwan. It is then determined whether the typhoon approaches the study area according to the typhoon track predicted by the CWB. When a typhoon hits Taiwan, various data are received from sensor instruments, including the ground precipitation data, typhoon climatological data, and radar reflectivity factor by using Weather Surveillance Radar, 1988, Doppler (WSR-88D) products. The study site was Shihmen Catchment. A maximum of 10 typhoon events from 2000 to 2010 were collected. Regarding the model construction, the input combinations of the ground precipitations and reflectivity factors over the catchment functioned as optimal input variables. To verify the practicability of the ANFIS-based TERN model, Typhoon Krosa, which hit Taiwan in 2007, was simulated. The results demonstrated that the proposed methodology of real-time rainfall forecasts during typhoon warning periods yielded favorable performance levels, reliably predicting results regarding 1 h to 6 h forecasting horizons.

  13. Weather radar research at the USA's storm laboratory

    NASA Technical Reports Server (NTRS)

    Doviak, R. J.

    1982-01-01

    Radar research that is directed toward improving storm forecasts and hazard warnings and studying lightning is discussed. The two moderately sensitive Doppler weather radars in central Oklahoma, with their wide dynamic range, have demonstrated the feasibility of mapping wind fields in all weather conditions from the clear skies of quiescent air and disturbed prestorm air near the earth's surface to the optically opaque interior of severe and sometimes tornadic thunderstorms. Observations and analyses of Doppler weather radar data demonstrate that improved warning of severe storm phenomena and improved short-term forecast of storms may be available when Doppler techniques are well integrated into the national network of weather radars. When used in combination with other sensors, it provides an opportunity to learn more about the complex interrelations between the wind, water, and electricity in storms.

  14. Correlation of S-Band Weather Radar Reflectivity and ACTS Propagation Data in Florida

    NASA Technical Reports Server (NTRS)

    Wolfe, Eric E.; Flikkema, Paul G.; Henning, Rudolf E.

    1997-01-01

    Previous work has shown that Ka-band attenuation due to rainfall and corresponding S-band reflectivity are highly correlated. This paper reports on work whose goal is to determine the feasibility of estimation and, by extension, prediction of one parameter from the other using the Florida ACTS propagation terminal (APT) and the nearby WSR-88D S-band Doppler weather radar facility operated by the National Weather Service. This work is distinguished from previous efforts in this area by (1) the use of a single-polarized radar, preventing estimation of the drop size distribution (e.g., with dual polarization) and (2) the fact that the radar and APT sites are not co-located. Our approach consists of locating the radar volume elements along the satellite slant path and then, from measured reflectivity, estimating the specific attenuation for each associated path segment. The sum of these contributions yields an estimation of the millimeter-wave attenuation on the space-ground link. Seven days of data from both systems are analyzed using this procedure. The results indicate that definite correlation of S-band reflectivity and Ka-band attenuation exists even under the restriciton of this experiment. Based on these results, it appears possible to estimate Ka-band attenuation using widely available operational weather radar data. Conversely, it may be possible to augment current radar reflectivity data and coverage with low-cost attenuation or sky temperature data to improve the estimation of rain rates.

  15. Adjustment of wind-drift effect for real-time systematic error correction in radar rainfall data

    NASA Astrophysics Data System (ADS)

    Dai, Qiang; Han, Dawei; Zhuo, Lu; Huang, Jing; Islam, Tanvir; Zhang, Shuliang

    An effective bias correction procedure using gauge measurement is a significant step for radar data processing to reduce the systematic error in hydrological applications. In these bias correction methods, the spatial matching of precipitation patterns between radar and gauge networks is an important premise. However, the wind-drift effect on radar measurement induces an inconsistent spatial relationship between radar and gauge measurements as the raindrops observed by radar do not fall vertically to the ground. Consequently, a rain gauge does not correspond to the radar pixel based on the projected location of the radar beam. In this study, we introduce an adjustment method to incorporate the wind-drift effect into a bias correlation scheme. We first simulate the trajectory of raindrops in the air using downscaled three-dimensional wind data from the weather research and forecasting model (WRF) and calculate the final location of raindrops on the ground. The displacement of rainfall is then estimated and a radar-gauge spatial relationship is reconstructed. Based on this, the local real-time biases of the bin-average radar data were estimated for 12 selected events. Then, the reference mean local gauge rainfall, mean local bias, and adjusted radar rainfall calculated with and without consideration of the wind-drift effect are compared for different events and locations. There are considerable differences for three estimators, indicating that wind drift has a considerable impact on the real-time radar bias correction. Based on these facts, we suggest bias correction schemes based on the spatial correlation between radar and gauge measurements should consider the adjustment of the wind-drift effect and the proposed adjustment method is a promising solution to achieve this.

  16. High-resolution Rainfall Mapping in Dallas-Fort Worth (DFW) Urban Network of Radars at Multiple Frequencies

    NASA Astrophysics Data System (ADS)

    Chandra, Chandrasekar V.; Chen*, Haonan

    2015-04-01

    Urban flash flood is one of the most commonly encountered hazardous weather phenomena. Unfortunately, the rapid urbanization has made the densely populated areas even more vulnerable to flood risks. Hence, accurate and timely monitoring of rainfall at high spatiotemporal resolution is critical to severe weather warning and civil defense, especially in urban areas. However, it is still challenging to produce high-resolution products based on the large S-band National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD), due to the sampling limitations and Earth curvature effect. Since 2012, the U.S. National Science Foundation Engineering Research Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) has initiated the development of Dallas-Fort Worth (DFW) radar remote sensing network for urban weather hazards mitigation. The DFW urban radar network consists of a combination of high-resolution X-band radars and a standard NWS NEXRAD radar operating at S-band frequency. High-resolution quantitative precipitation estimation (QPE) is one of the major research goals in the deployment of this urban radar network. It has been shown in the literature that the dual-polarization radar techniques can improve the QPE accuracy over traditional single-polarization radars by rendering more measurements to enhance the data quality, providing more information about rain drop size distribution (DSD), and implying more characteristics of different hydrometeor types. This paper will present the real-time dual-polarization CASA DFW QPE system, which is developed via fusion of observations from both the high-resolution X band radar network and the S-band NWS radar. The specific dual-polarization rainfall algorithms at different frequencies (i.e., S- and X-band) will be described in details. In addition, the fusion methodology combining observations at different temporal resolution will be presented. In order to demonstrate the capability of rainfall

  17. Sever Hazards Prediction Method by Using Phased Array Weather Radar (PAWR)

    NASA Astrophysics Data System (ADS)

    Michimoto, K.

    2014-12-01

    We are now research several sever hazards of meteorological phenomena, for example, thunderstorm, hail, heavy rain-fall, tornado, etc., by using Phased Array Weather Radar (PAWR). In this paper, we present our analyses between PAWRs echo data temporal variations and thunderstorms lightning activity, hail fall and/or heavy rain-fall rate, etc. We will develop nowcast and/or forecast methods of sever hazards and, in near future, we will prepare new prediction numerical model of sever hazards by using CReSS (Cloud Resolving Storm Simulator).

  18. Phase noise effects on turbulent weather radar spectrum parameter estimation

    NASA Technical Reports Server (NTRS)

    Lee, Jonggil; Baxa, Ernest G., Jr.

    1990-01-01

    Accurate weather spectrum moment estimation is important in the use of weather radar for hazardous windshear detection. The effect of the stable local oscillator (STALO) instability (jitter) on the spectrum moment estimation algorithm is investigated. Uncertainty in the stable local oscillator will affect both the transmitted signal and the received signal since the STALO provides transmitted and reference carriers. The proposed approach models STALO phase jitter as it affects the complex autocorrelation of the radar return. The results can therefore by interpreted in terms of any source of system phase jitter for which the model is appropriate and, in particular, may be considered as a cumulative effect of all radar system sources.

  19. High resolution X-Band radar rainfall estimates for a Mediterranean to hyper-arid transition area

    NASA Astrophysics Data System (ADS)

    Marra, Francesco; Lokshin, Anton; Notarpietro, Riccardo; Gabella, Marco; Branca, Marco; Bonfil, David; Morin, Efrat

    2015-04-01

    Weather radars provide rainfall estimates with high spatial and temporal resolutions over wide areas. X-Band weather radars are of relatively low-cost and easy to be handled and maintained, moreover they offer extremely high spatial and temporal resolutions and are therefore object of particular interest. Main drawback of these instruments lies on the quantitative accuracy, that can be significantly affected by atmospheric attenuation. Distributed rainfall information is a key issue when hydrological applications are needed for small space-time scale phenomena such as flash floods and debris flows. Moreover, such detailed measurements represent a great benefit for agricultural management of areas characterized by substantial rainfall variability. Two single polarization, single elevation, non-Doppler X-Band weather radars are operational since Oct-2012 in the northern Negev (Israel). Mean annual precipitation over the area drops dramatically from 500 mm/yr at the Mediterranean coast to less than 50 mm/yr at the hyper-arid region near the Dead Sea in less than a 100 km distance. The dryer region close to the Dead Sea is prone to flash floods that often cause casualties and severe damage while the western Mediterranean region is extensively used for agricultural purposes. Measures from a C-Band weather radar located 40-120 km away and from a sparse raingauge network (density ~1gauge/450km2) are also available. C-Band rainfall estimates are corrected using combined physically-based and empirical adjustment of data. The aim of this study is to assess the quantitative accuracy of X-Band rainfall estimates with respect to the combined use of in situ measurements and C-Band observations. Results from a set of storms occurred during the first years of measurements are discussed paying particular attention to: (i) wet radome attenuation, (ii) range dependent degradation including attenuation along the path and (iii) systematic effects related to the Mediterranean to hyper

  20. Close-range radar rainfall estimation and error analysis

    NASA Astrophysics Data System (ADS)

    van de Beek, C. Z.; Leijnse, H.; Hazenberg, P.; Uijlenhoet, R.

    2012-04-01

    It is well-known that quantitative precipitation estimation (QPE) is affected by many sources of error. The most important of these are 1) radar calibration, 2) wet radome attenuation, 3) rain attenuation, 4) vertical profile of reflectivity, 5) variations in drop size distribution, and 6) sampling effects. The study presented here is an attempt to separate and quantify these sources of error. For this purpose, QPE is performed very close to the radar (~1-2 km) so that 3), 4), and 6) will only play a minor role. Error source 5) can be corrected for because of the availability of two disdrometers (instruments that measure the drop size distribution). A 3-day rainfall event (25-27 August 2010) that produced more than 50 mm in De Bilt, The Netherlands is analyzed. Radar, rain gauge, and disdrometer data from De Bilt are used for this. It is clear from the analyses that without any corrections, the radar severely underestimates the total rain amount (only 25 mm). To investigate the effect of wet radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation up to ~4 dB. The calibration of the radar is checked by looking at received power from the sun. This turns out to cause another 1 dB of underestimation. The effect of variability of drop size distributions is shown to cause further underestimation. Correcting for all of these effects yields a good match between radar QPE and gauge measurements.

  1. Multiscale Hydrologic Evaluation of Radar Rainfall for Flow Simulations

    NASA Astrophysics Data System (ADS)

    Quintero, Felipe; Krajewski, Witold; Seo, Bong-Chul; Mantilla, Ricardo

    2016-04-01

    We made an evaluation of the performance of a hydrologic model to produce real-time flow forecasts. The model has been developed by the Iowa Flood Center (IFC), and it is implemented operationally to produce streamflow forecast for the communities of the State of Iowa in the United States. The model parameters are calibration-free. It has a parsimonious structure, that reproduces the more significant processes involved in the transformation from rainfall to runoff. The operational model uses a rainfall forcing produced by IFC, derived from the combination of rainfall fields of seven NEXRAD radars. However, this rainfall forcing does not include bias adjustment from rain gauges, due to the non-existence of a raingage network that enable the correction in real-time. In consideration, the model is also run offline using bias-adjusted rainfall products as Stage IV, and more recently MRMS. We used an extensive record of five years of IFC rainfall product and Stage IV, to evaluate the performance of the hydrologic model and the sensitivity of the flow simulations to model input. The model is not calibrated to any particular rainfall product. The distributed structure of the model allows to obtain results at any channel of the drainage network. We obtained simulated hydrographs at about 150 locations with different sub-basin spatial scales, where there are available USGS gages with streamflow observations. We obtained error metrics as Nash Sutcliffe efficiency and root mean square error, by comparing flow simulations to observations. We evaluated also the number of occurrences of hits and false alarms of discharge forecasts exceeding flood stage.

  2. Evaluation of polarimetric parameters from a new dual-polarization C-band weather radar in an alpine region

    NASA Astrophysics Data System (ADS)

    Paulitsch, H.; Teschl, F.; Teschl, R.

    2009-04-01

    The first weather radar with dual polarization capabilities was recently installed in Austria. In contrast to conventional weather radars, where the reflectivity is measured in one polarization plane only, a dual polarization radar provides transmission in either horizontal, vertical, or both polarizations while receiving both the horizontal and vertical channels simultaneously. The back-scatter from precipitation particles is different for horizontal and vertical polarization, because these particles are usually far from being spherical. Information on size, shape, and material density of precipitation particles is obtained by comparing the reflected horizontal and vertical power returns and their ratio and correlation. The use of polarimetric radar variables can therefore increase the accuracy of the rain rate estimation compared to standard Z-R relationship of non-polarimetric radars. For the new weather radar different polarimetric rain rate estimators, which are based on the horizontal polarization radar reflectivity, Zh, the differential reflectivity, Zdr, and the specific differential phase shift, Kdp, are used. The rain rate estimators are further combined with an attenuation correction schema. In this study several radar observations of rainfall events are used to test the rain rate estimators and the attenuation correction. The results of the different algorithm are presented and a comparison with rain gauge measurements is made. Also the operational quality of the radar parameters is discussed and the implication of radar measurement errors on the accuracy of polarimetric rain rate estimations is shown.

  3. Radar volume reflectivity estimation using an array of ground-based rainfall drop size detectors

    NASA Astrophysics Data System (ADS)

    Lane, John; Merceret, Francis; Kasparis, Takis; Roy, D.; Muller, Brad; Jones, W. Linwood

    2000-08-01

    Rainfall drop size distribution (DSD) measurements made by single disdrometers at isolated ground sites have traditionally been used to estimate the transformation between weather radar reflectivity Z and rainfall rate R. Despite the immense disparity in sampling geometries, the resulting Z-R relation obtained by these single point measurements has historically been important in the study of applied radar meteorology. Simultaneous DSD measurements made at several ground sites within a microscale area may be used to improve the estimate of radar reflectivity in the air volume surrounding the disdrometer array. By applying the equations of motion for non-interacting hydrometers, a volume estimate of Z is obtained from the array of ground based disdrometers by first calculating a 3D drop size distribution. The 3D-DSD model assumes that only gravity and terminal velocity due to atmospheric drag within the sampling volume influence hydrometer dynamics. The sampling volume is characterized by wind velocities, which are input parameters to the 3D-DSD model, composed of vertical and horizontal components. Reflectivity data from four consecutive WSR-88D volume scans, acquired during a thunderstorm near Melbourne, FL on June 1, 1997, are compared to data processed using the 3D-DSD model and data form three ground based disdrometers of a microscale array.

  4. Inter-comparison of radar rainfall rate using Constant Altitude Plan Position Indicator and hybrid surface rainfall maps

    NASA Astrophysics Data System (ADS)

    Kwon, Soohyun; Jung, Sung-Hwa; Lee, GyuWon

    2015-12-01

    Ground clutter and beam blockage caused by complex terrain deteriorates the accuracy of radar quantitative precipitation estimations (QPE). To improve radar QPE, we have developed a technique for radar rainfall estimation, the Kyungpook National University Hybrid Surface Rainfall (KHSR), based on a two-dimensional hybrid surface consisting of the lowest radar bins that are immune to ground clutter, beam blockage, and non-meteorological echoes. The KHSR map is a composite of a ground echo mask, a beam blockage mask, and a rain echo mask, and it was applied to an operational S-band dual-polarimetric radar that scans six PPIs at a low elevation angle every 2.5 min. By using three rainfall estimators, R(ZH), R(ZH, ZDR), and R(ZH, ξDR), this technique was compared with an operational Constant Altitude Plan Position Indicator (CAPPI) QPE of the Korea Meteorological Administration during a summer season from June-August 2012. In comparison with CAPPI, KHSR shows improved rainfall estimates for three algorithms, and it was more effective with dual-polarimetric rainfall algorithms than with single polarimetric rainfall algorithms. Error increased with increasing range from radar, but this increase was more rapid using CAPPI than using KHSR. KHSR using the R(ZH, ZDR) algorithm was the most accurate long range (>100 km from the radar) estimator.

  5. Optimizing weather radar observations using an adaptive multiquadric surface fitting algorithm

    NASA Astrophysics Data System (ADS)

    Martens, Brecht; Cabus, Pieter; De Jongh, Inge; Verhoest, Niko

    2013-04-01

    Real time forecasting of river flow is an essential tool in operational water management. Such real time modelling systems require well calibrated models which can make use of spatially distributed rainfall observations. Weather radars provide spatial data, however, since radar measurements are sensitive to a large range of error sources, often a discrepancy between radar observations and ground-based measurements, which are mostly considered as ground truth, can be observed. Through merging ground observations with the radar product, often referred to as data merging, one may force the radar observations to better correspond to the ground-based measurements, without losing the spatial information. In this paper, radar images and ground-based measurements of rainfall are merged based on interpolated gauge-adjustment factors (Moore et al., 1998; Cole and Moore, 2008) or scaling factors. Using the following equation, scaling factors (C(xα)) are calculated at each position xα where a gauge measurement (Ig(xα)) is available: Ig(xα)+-? C (xα) = Ir(xα)+ ? (1) where Ir(xα) is the radar-based observation in the pixel overlapping the rain gauge and ? is a constant making sure the scaling factor can be calculated when Ir(xα) is zero. These scaling factors are interpolated on the radar grid, resulting in a unique scaling factor for each pixel. Multiquadric surface fitting is used as an interpolation algorithm (Hardy, 1971): C*(x0) = aTv + a0 (2) where C*(x0) is the prediction at location x0, the vector a (Nx1, with N the number of ground-based measurements used) and the constant a0 parameters describing the surface and v an Nx1 vector containing the (Euclidian) distance between each point xα used in the interpolation and the point x0. The parameters describing the surface are derived by forcing the surface to be an exact interpolator and impose that the sum of the parameters in a should be zero. However, often, the surface is allowed to pass near the observations (i

  6. Quantitative precipitation estimation for an X-band weather radar network

    NASA Astrophysics Data System (ADS)

    Chen, Haonan

    Currently, the Next Generation (NEXRAD) radar network, a joint effort of the U.S. Department of Commerce (DOC), Defense (DOD), and Transportation (DOT), provides radar data with updates every five-six minutes across the United States. This network consists of about 160 S-band (2.7 to 3.0 GHz) radar sites. At the maximum NEXRAD range of 230 km, the 0.5 degree radar beam is about 5.4 km above ground level (AGL) because of the effect of earth curvature. Consequently, much of the lower atmosphere (1-3 km AGL) cannot be observed by the NEXRAD. To overcome the fundamental coverage limitations of today's weather surveillance radars, and improve the spatial and temporal resolution issues, the National Science Foundation Engineering Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) was founded to revolutionize weather sensing in the lower atmosphere by deploying a dense network of shorter-range, low-power X-band dual-polarization radars. The distributed CASA radars are operating collaboratively to adapt the changing atmospheric conditions. Accomplishments and breakthroughs after five years operation have demonstrated the success of CASA program. Accurate radar quantitative precipitation estimation (QPE) has been pursued since the beginning of weather radar. For certain disaster prevention applications such as flash flood and landslide forecasting, the rain rate must however be measured at a high spatial and temporal resolution. To this end, high-resolution radar QPE is one of the major research activities conducted by the CASA community. A radar specific differential propagation phase (Kdp)-based QPE methodology has been developed in CASA. Unlike the rainfall estimation based on the power terms such as radar reflectivity (Z) and differential reflectivity (Zdr), Kdp-based QPE is less sensitive to the path attenuation, drop size distribution (DSD), and radar calibration errors. The CASA Kdp-based QPE system is also immune to the partial beam

  7. Mapping wintering waterfowl distributions using weather surveillance radar.

    PubMed

    Buler, Jeffrey J; Randall, Lori A; Fleskes, Joseph P; Barrow, Wylie C; Bogart, Tianna; Kluver, Daria

    2012-01-01

    The current network of weather surveillance radars within the United States readily detects flying birds and has proven to be a useful remote-sensing tool for ornithological study. Radar reflectivity measures serve as an index to bird density and have been used to quantitatively map landbird distributions during migratory stopover by sampling birds aloft at the onset of nocturnal migratory flights. Our objective was to further develop and validate a similar approach for mapping wintering waterfowl distributions using weather surveillance radar observations at the onset of evening flights. We evaluated data from the Sacramento, CA radar (KDAX) during winters 1998-1999 and 1999-2000. We determined an optimal sampling time by evaluating the accuracy and precision of radar observations at different times during the onset of evening flight relative to observed diurnal distributions of radio-marked birds on the ground. The mean time of evening flight initiation occurred 23 min after sunset with the strongest correlations between reflectivity and waterfowl density on the ground occurring almost immediately after flight initiation. Radar measures became more spatially homogeneous as evening flight progressed because birds dispersed from their departure locations. Radars effectively detected birds to a mean maximum range of 83 km during the first 20 min of evening flight. Using a sun elevation angle of -5° (28 min after sunset) as our optimal sampling time, we validated our approach using KDAX data and additional data from the Beale Air Force Base, CA (KBBX) radar during winter 1998-1999. Bias-adjusted radar reflectivity of waterfowl aloft was positively related to the observed diurnal density of radio-marked waterfowl locations on the ground. Thus, weather radars provide accurate measures of relative wintering waterfowl density that can be used to comprehensively map their distributions over large spatial extents. PMID:22911816

  8. Mapping wintering waterfowl distributions using weather surveillance radar

    USGS Publications Warehouse

    Buler, Jeffrey J.; Randall, Lori A.; Fleskes, Joseph P.; Barrow, Wylie C.; Bogart, Tianna; Kluver, Daria

    2012-01-01

    The current network of weather surveillance radars within the United States readily detects flying birds and has proven to be a useful remote-sensing tool for ornithological study. Radar reflectivity measures serve as an index to bird density and have been used to quantitatively map landbird distributions during migratory stopover by sampling birds aloft at the onset of nocturnal migratory flights. Our objective was to further develop and validate a similar approach for mapping wintering waterfowl distributions using weather surveillance radar observations at the onset of evening flights. We evaluated data from the Sacramento, CA radar (KDAX) during winters 1998–1999 and 1999–2000. We determined an optimal sampling time by evaluating the accuracy and precision of radar observations at different times during the onset of evening flight relative to observed diurnal distributions of radio-marked birds on the ground. The mean time of evening flight initiation occurred 23 min after sunset with the strongest correlations between reflectivity and waterfowl density on the ground occurring almost immediately after flight initiation. Radar measures became more spatially homogeneous as evening flight progressed because birds dispersed from their departure locations. Radars effectively detected birds to a mean maximum range of 83 km during the first 20 min of evening flight. Using a sun elevation angle of -5° (28 min after sunset) as our optimal sampling time, we validated our approach using KDAX data and additional data from the Beale Air Force Base, CA (KBBX) radar during winter 1998–1999. Bias-adjusted radar reflectivity of waterfowl aloft was positively related to the observed diurnal density of radio-marked waterfowl locations on the ground. Thus, weather radars provide accurate measures of relative wintering waterfowl density that can be used to comprehensively map their distributions over large spatial extents.

  9. Chemical weathering of granite under acid rainfall environment, Korea

    NASA Astrophysics Data System (ADS)

    Lee, Seung Yeop; Kim, Soo Jin; Baik, Min Hoon

    2008-08-01

    Chemical weathering was investigated by collecting samples from five selected weathering profiles in a high elevation granitic environment located in Seoul, Korea. The overall changes of chemistry and mineralogical textures were examined reflecting weathering degrees of the samples, using polarization microscopy, X-ray diffraction (XRD), electron probe micro analysis (EPMA), X-ray fluorescence spectroscopy (XRF), and inductively coupled plasma-mass spectroscopy (ICP-MS). The chemical distribution in the weathering profiles shows that few trace elements are slightly immobile, whereas most major (particularly Ca and Na) and trace elements are mobile from the beginning of the granite weathering. On the other hand, there were mineralogical changes initiated from a plagioclase breakdown, which shows a characteristic circular dissolved pattern caused by a preferential leaching of Ca cation along grain boundaries and zoning. The biotite in that region is also supposed to be sensitive to exterior environmental condition and may be easily dissolved by acidic percolated water. As a result, it seems that some rock-forming minerals in the granitic rock located in Seoul are significantly unstable due to the environmental condition of acidic rainfall and steep slopes, where they are susceptible to be dissolved incongruently leading some elements to be highly depleted.

  10. The Use of Radar to Improve Rainfall Estimation over the Tennessee and San Joaquin River Valleys

    NASA Technical Reports Server (NTRS)

    Petersen, Walter A.; Gatlin, Patrick N.; Felix, Mariana; Carey, Lawrence D.

    2010-01-01

    This slide presentation provides an overview of the collaborative radar rainfall project between the Tennessee Valley Authority (TVA), the Von Braun Center for Science & Innovation (VCSI), NASA MSFC and UAHuntsville. Two systems were used in this project, Advanced Radar for Meteorological & Operational Research (ARMOR) Rainfall Estimation Processing System (AREPS), a demonstration project of real-time radar rainfall using a research radar and NEXRAD Rainfall Estimation Processing System (NREPS). The objectives, methodology, some results and validation, operational experience and lessons learned are reviewed. The presentation. Another project that is using radar to improve rainfall estimations is in California, specifically the San Joaquin River Valley. This is part of a overall project to develop a integrated tool to assist water management within the San Joaquin River Valley. This involves integrating several components: (1) Radar precipitation estimates, (2) Distributed hydro model, (3) Snowfall measurements and Surface temperature / moisture measurements. NREPS was selected to provide precipitation component.

  11. Using raindrop size distributions from different types of disdrometer to establish weather radar algorithms

    NASA Astrophysics Data System (ADS)

    Baldini, Luca; Adirosi, Elisa; Roberto, Nicoletta; Vulpiani, Gianfranco; Russo, Fabio; Napolitano, Francesco

    2015-04-01

    Radar precipitation retrieval uses several relationships that parameterize precipitation properties (like rainfall rate and liquid water content and attenuation (in case of radars at attenuated frequencies such as those at C- and X- band) as a function of combinations of radar measurements. The uncertainty in such relations highly affects the uncertainty precipitation and attenuation estimates. A commonly used method to derive such relationships is to apply regression methods to precipitation measurements and radar observables simulated from datasets of drop size distributions (DSD) using microphysical and electromagnetic assumptions. DSD datasets are determined both by theoretical considerations (i.e. based on the assumption that the radar always samples raindrops whose sizes follow a gamma distribution) or from experimental measurements collected throughout the years by disdrometers. In principle, using long-term disdrometer measurements provide parameterizations more representative of a specific climatology. However, instrumental errors, specific of a disdrometer, can affect the results. In this study, different weather radar algorithms resulting from DSDs collected by diverse types of disdrometers, namely 2D video disdrometer, first and second generation of OTT Parsivel laser disdrometer, and Thies Clima laser disdrometer, in the area of Rome (Italy) are presented and discussed to establish at what extent dual-polarization radar algorithms derived from experimental DSD datasets are influenced by the different error structure of the different type of disdrometers used to collect the data.

  12. New Approaches to Rainfall and Flood Frequency Analysis Using High Resolution Radar Rainfall Fields and Stochastic Storm Transposition

    NASA Astrophysics Data System (ADS)

    Wright, D. B.; Smith, J. A.; Villarini, G.; Baeck, M. L.

    2012-12-01

    Conventional techniques for rainfall and flood frequency analysis in small watersheds involve a variety of assumptions regarding the spatial and temporal structure of extreme rainfall systems as well as how resulting runoff moves through the drainage network. These techniques were developed at a time when observational and computational resources were limited. They continue to be used in practice though their validity has not been fully examined. New observational and computational resources such as high-resolution radar rainfall estimates and distributed hydrologic models allow us to examine these assumptions and to develop alternative methods for estimating flood risk. We have developed a high-resolution (1 square km, 15-minute resolution) radar rainfall dataset for the 2001-2010 period using the Hydro-NEXRAD processing system, which has been bias corrected using a dense network of 71 rain gages in the Charlotte metropolitan area. The accuracy of the bias-corrected radar rainfall estimates compare favorably with rain gage measurements. The radar rainfall dataset is used in a stochastic storm transposition framework to estimate the frequency of extreme rainfall for urban watersheds ranging the point/radar pixel scale up to 240 square km, and can be combined with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model to estimate flood frequency analysis. The results of these frequency analyses can be compared against the results of conventional methods such as the NOAA Atlas 14 precipitation frequency estimates and peak discharge estimates prepared by FEMA and the North Carolina state government.

  13. Quantifying radar-rainfall uncertainties in urban drainage flow modelling

    NASA Astrophysics Data System (ADS)

    Rico-Ramirez, M. A.; Liguori, S.; Schellart, A. N. A.

    2015-09-01

    This work presents the results of the implementation of a probabilistic system to model the uncertainty associated to radar rainfall (RR) estimates and the way this uncertainty propagates through the sewer system of an urban area located in the North of England. The spatial and temporal correlations of the RR errors as well as the error covariance matrix were computed to build a RR error model able to generate RR ensembles that reproduce the uncertainty associated with the measured rainfall. The results showed that the RR ensembles provide important information about the uncertainty in the rainfall measurement that can be propagated in the urban sewer system. The results showed that the measured flow peaks and flow volumes are often bounded within the uncertainty area produced by the RR ensembles. In 55% of the simulated events, the uncertainties in RR measurements can explain the uncertainties observed in the simulated flow volumes. However, there are also some events where the RR uncertainty cannot explain the whole uncertainty observed in the simulated flow volumes indicating that there are additional sources of uncertainty that must be considered such as the uncertainty in the urban drainage model structure, the uncertainty in the urban drainage model calibrated parameters, and the uncertainty in the measured sewer flows.

  14. Comparison Between Radar and Automatic Weather Station Refractivity Variability

    NASA Astrophysics Data System (ADS)

    Hallali, Ruben; Dalaudier, Francis; Parent du Chatelet, Jacques

    2016-08-01

    Weather radars measure changes in the refractive index of air in the atmospheric boundary layer. The technique uses the phase of signals from ground targets located around the radar to provide information on atmospheric refractivity related to meteorological quantities such as temperature, pressure and humidity. The approach has been successfully implemented during several field campaigns using operational S-band radars in Canada, UK, USA and France. In order to better characterize the origins of errors, a recent study has simulated temporal variations of refractivity based on Automatic Weather Station (AWS) measurements. This reveals a stronger variability of the refractivity during the summer and in the afternoon when the refractivity is the most sensitive to humidity, probably because of turbulence close to the ground. This raises the possibility of retrieving information on the turbulent state of the atmosphere from the variability in radar refractivity. An analysis based on a 1-year dataset from the operational C-band radar at Trappes (near Paris, France) and AWS refractivity variability measurements was used to measure those temporal and spatial variabilities. Particularly during summer, a negative bias increasing with range is observed between radar and AWS estimations, and is well explained by a model based on Taylor's hypotheses. The results demonstrate the possibility of establishing, depending on season, a quantitative and qualitative link between radar and AWS refractivity variability that reflects low-level coherent turbulent structures.

  15. Comparison Between Radar and Automatic Weather Station Refractivity Variability

    NASA Astrophysics Data System (ADS)

    Hallali, Ruben; Dalaudier, Francis; Parent du Chatelet, Jacques

    2016-03-01

    Weather radars measure changes in the refractive index of air in the atmospheric boundary layer. The technique uses the phase of signals from ground targets located around the radar to provide information on atmospheric refractivity related to meteorological quantities such as temperature, pressure and humidity. The approach has been successfully implemented during several field campaigns using operational S-band radars in Canada, UK, USA and France. In order to better characterize the origins of errors, a recent study has simulated temporal variations of refractivity based on Automatic Weather Station (AWS) measurements. This reveals a stronger variability of the refractivity during the summer and in the afternoon when the refractivity is the most sensitive to humidity, probably because of turbulence close to the ground. This raises the possibility of retrieving information on the turbulent state of the atmosphere from the variability in radar refractivity. An analysis based on a 1-year dataset from the operational C-band radar at Trappes (near Paris, France) and AWS refractivity variability measurements was used to measure those temporal and spatial variabilities. Particularly during summer, a negative bias increasing with range is observed between radar and AWS estimations, and is well explained by a model based on Taylor's hypotheses. The results demonstrate the possibility of establishing, depending on season, a quantitative and qualitative link between radar and AWS refractivity variability that reflects low-level coherent turbulent structures.

  16. Cross-validation Methodology between Ground and GPM Satellite-based Radar Rainfall Product over Dallas-Fort Worth (DFW) Metroplex

    NASA Astrophysics Data System (ADS)

    Chen, H.; Chandrasekar, V.; Biswas, S.

    2015-12-01

    Over the past two decades, a large number of rainfall products have been developed based on satellite, radar, and/or rain gauge observations. However, to produce optimal rainfall estimation for a given region is still challenging due to the space time variability of rainfall at many scales and the spatial and temporal sampling difference of different rainfall instruments. In order to produce high-resolution rainfall products for urban flash flood applications and improve the weather sensing capability in urban environment, the center for Collaborative Adaptive Sensing of the Atmosphere (CASA), in collaboration with National Weather Service (NWS) and North Central Texas Council of Governments (NCTCOG), has developed an urban radar remote sensing network in DFW Metroplex. DFW is the largest inland metropolitan area in the U.S., that experiences a wide range of natural weather hazards such as flash flood and hailstorms. The DFW urban remote sensing network, centered by the deployment of eight dual-polarization X-band radars and a NWS WSR-88DP radar, is expected to provide impacts-based warning and forecasts for benefit of the public safety and economy. High-resolution quantitative precipitation estimation (QPE) is one of the major goals of the development of this urban test bed. In addition to ground radar-based rainfall estimation, satellite-based rainfall products for this area are also of interest for this study. Typical example is the rainfall rate product produced by the Dual-frequency Precipitation Radar (DPR) onboard Global Precipitation Measurement (GPM) Core Observatory satellite. Therefore, cross-comparison between ground and space-based rainfall estimation is critical to building an optimal regional rainfall system, which can take advantages of the sampling differences of different sensors. This paper presents the real-time high-resolution QPE system developed for DFW urban radar network, which is based upon the combination of S-band WSR-88DP and X

  17. ASSIMILATION OF DOPPLER RADAR DATA INTO NUMERICAL WEATHER MODELS

    SciTech Connect

    Chiswell, S.; Buckley, R.

    2009-01-15

    During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has made higher

  18. Impact of complexity of radar rainfall uncertainty model on flow simulation

    NASA Astrophysics Data System (ADS)

    Dai, Qiang; Han, Dawei; Zhuo, Lu; Huang, Jing; Islam, Tanvir; Srivastava, Prashant K.

    2015-07-01

    A large number of radar rainfall uncertainty (RRU) models have been proposed due to many error sources in weather radar measurements. It is recognized that these models should be integrated into overall uncertainty analysis schemes with other kinds of model uncertainties such as model parameter uncertainty when the radar rainfall is applied in hydrological modeling. We expect that the RRU model can be expressed in a mathematically extensible and simple format. However, the complexity of the RRU has been growing as more and more factors are considered such as spatio-temporal dependence and non-Gaussian distribution. This study analyzes how the RRU propagates through a hydrological model (the Xinanjiang model) and investigates which features of the RRU model have significant impacts on flow simulation. A RRU model named Multivariate Distributed Ensemble Generator (MDEG) is implemented in the Brue catchment in England under different model complexities. The generated ensemble rainfall values by MDEG are then input into the Xinanjiang model to produce uncertainty bands of ensemble flows. Comparison of five important indicators that describe the characteristics of uncertainty bands shows that the ensemble flows generated by MDEG with non-Gaussian marginal and joint distributions are close to the ones with Gaussian distributions. In addition, the dispersion of the uncertainty bands increases dramatically with the growth of the MDEG model complexity. It is concluded that the Gaussian marginal distribution and spatio-temporal dependence using Gaussian copula is considered to be the preferred configuration of the MDEG model for hydrological model uncertainty analysis. Further studies should be carried out in a variety of catchments under different climate conditions and geographical locations to check if the conclusion is valid beyond the Brue catchment under the British climate.

  19. Doppler weather radar with predictive wind shear detection capabilities

    NASA Technical Reports Server (NTRS)

    Kuntman, Daryal

    1991-01-01

    The status of Bendix research on Doppler weather radar with predictive wind shear detection capability is given in viewgraph form. Information is given on the RDR-4A, a fully coherent, solid state transmitter having Doppler turbulence capability. Frequency generation data, plans, modifications, system characteristics and certification requirements are covered.

  20. Demonstration of radar reflector detection and ground clutter suppression using airborne weather and mapping radar

    NASA Technical Reports Server (NTRS)

    Anderson, D. J.; Bull, J. S.; Chisholm, J. P.

    1982-01-01

    A navigation system which utilizes minimum ground-based equipment is especially advantageous to helicopters, which can make off-airport landings. Research has been conducted in the use of weather and mapping radar to detect large radar reflectors overland for navigation purposes. As initial studies have not been successful, investigations were conducted regarding a new concept for the detection of ground-based radar reflectors and eliminating ground clutter, using a device called an echo processor (EP). A description is presented of the problems associated with detecting radar reflectors overland, taking into account the EP concept and the results of ground- and flight-test investigations. The echo processor concept was successfully demonstrated in detecting radar reflectors overland in a high-clutter environment. A radar reflector target size of 55 dBsm was found to be adequate for detection in an urban environment.

  1. Improved wet weather wastewater influent modelling at Viikinmäki WWTP by on-line weather radar information.

    PubMed

    Heinonen, M; Jokelainen, M; Fred, T; Koistinen, J; Hohti, H

    2013-01-01

    Municipal wastewater treatment plant (WWTP) influent is typically dependent on diurnal variation of urban production of liquid waste, infiltration of stormwater runoff and groundwater infiltration. During wet weather conditions the infiltration phenomenon typically increases the risk of overflows in the sewer system as well as the risk of having to bypass the WWTP. Combined sewer infrastructure multiplies the role of rainwater runoff in the total influent. Due to climate change, rain intensity and magnitude is tending to rise as well, which can already be observed in the normal operation of WWTPs. Bypass control can be improved if the WWTP is prepared for the increase of influent, especially if there is some storage capacity prior to the treatment plant. One option for this bypass control is utilisation of on-line weather-radar-based forecast data of rainfall as an input for the on-line influent model. This paper reports the Viikinmäki WWTP wet weather influent modelling project results where gridded exceedance probabilities of hourly rainfall accumulations for the next 3 h from the Finnish Meteorological Institute are utilised as on-line input data for the influent model. PMID:23925175

  2. Improved radar data processing algorithms for quantitative rainfall estimation in real time.

    PubMed

    Krämer, S; Verworn, H R

    2009-01-01

    This paper describes a new methodology to process C-band radar data for direct use as rainfall input to hydrologic and hydrodynamic models and in real time control of urban drainage systems. In contrast to the adjustment of radar data with the help of rain gauges, the new approach accounts for the microphysical properties of current rainfall. In a first step radar data are corrected for attenuation. This phenomenon has been identified as the main cause for the general underestimation of radar rainfall. Systematic variation of the attenuation coefficients within predefined bounds allows robust reflectivity profiling. Secondly, event specific R-Z relations are applied to the corrected radar reflectivity data in order to generate quantitative reliable radar rainfall estimates. The results of the methodology are validated by a network of 37 rain gauges located in the Emscher and Lippe river basins. Finally, the relevance of the correction methodology for radar rainfall forecasts is demonstrated. It has become clearly obvious, that the new methodology significantly improves the radar rainfall estimation and rainfall forecasts. The algorithms are applicable in real time. PMID:19587415

  3. Estimating subcatchment runoff coefficients using weather radar and a downstream runoff sensor.

    PubMed

    Ahm, Malte; Thorndahl, Søren; Rasmussen, Michael R; Bassø, Lene

    2013-01-01

    This paper presents a method for estimating runoff coefficients of urban drainage subcatchments based on a combination of high resolution weather radar data and flow measurements from a downstream runoff sensor. By utilising the spatial variability of the precipitation it is possible to estimate the runoff coefficients of the separate subcatchments. The method is demonstrated through a case study of an urban drainage catchment (678 ha) located in the city of Aarhus, Denmark. The study has proven that it is possible to use corresponding measurements of the relative rainfall distribution over the catchment and downstream runoff measurements to identify the runoff coefficients at subcatchment level. PMID:24056426

  4. Coupling Radar Rainfall to Hydrological Models for Water Abstraction Management

    NASA Astrophysics Data System (ADS)

    Asfaw, Alemayehu; Shucksmith, James; Smith, Andrea; MacDonald, Ken

    2015-04-01

    The impacts of climate change and growing water use are likely to put considerable pressure on water resources and the environment. In the UK, a reform to surface water abstraction policy has recently been proposed which aims to increase the efficiency of using available water resources whilst minimising impacts on the aquatic environment. Key aspects to this reform include the consideration of dynamic rather than static abstraction licensing as well as introducing water trading concepts. Dynamic licensing will permit varying levels of abstraction dependent on environmental conditions (i.e. river flow and quality). The practical implementation of an effective dynamic abstraction strategy requires suitable flow forecasting techniques to inform abstraction asset management. Potentially the predicted availability of water resources within a catchment can be coupled to predicted demand and current storage to inform a cost effective water resource management strategy which minimises environmental impacts. The aim of this work is to use a historical analysis of UK case study catchment to compare potential water resource availability using modelled dynamic abstraction scenario informed by a flow forecasting model, against observed abstraction under a conventional abstraction regime. The work also demonstrates the impacts of modelling uncertainties on the accuracy of predicted water availability over range of forecast lead times. The study utilised a conceptual rainfall-runoff model PDM - Probability-Distributed Model developed by Centre for Ecology & Hydrology - set up in the Dove River catchment (UK) using 1km2 resolution radar rainfall as inputs and 15 min resolution gauged flow data for calibration and validation. Data assimilation procedures are implemented to improve flow predictions using observed flow data. Uncertainties in the radar rainfall data used in the model are quantified using artificial statistical error model described by Gaussian distribution and

  5. Radar Scan Strategies for the Patrick Air Force Base Weather Surveillance Radar, Model-74C, Replacement

    NASA Technical Reports Server (NTRS)

    Short, David

    2008-01-01

    The 45th Weather Squadron (45 WS) is replacing the Weather Surveillance Radar, Model 74C (WSR-74C) at Patrick Air Force Base (PAFB), with a Doppler, dual polarization radar, the Radtec 43/250. A new scan strategy is needed for the Radtec 43/250, to provide high vertical resolution data over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) launch pads, while taking advantage of the new radar's advanced capabilities for detecting severe weather phenomena associated with convection within the 45 WS area of responsibility. The Applied Meteorology Unit (AMU) developed several scan strategies customized for the operational needs of the 45 WS. The AMU also developed a plan for evaluating the scan strategies in the period prior to operational acceptance, currently scheduled for November 2008.

  6. Exploring single polarization X-band weather radar potentials for local meteorological and hydrological applications

    NASA Astrophysics Data System (ADS)

    Lo Conti, Francesco; Francipane, Antonio; Pumo, Dario; Noto, Leonardo V.

    2015-12-01

    The aim of this study is to evaluate the potential use of a low-cost single polarization X-band weather radar, verified by a disdrometer and a dense rain gauge network, installed as a supporting tool for hydrological applications and for monitoring the urban area of Palermo (Italy). Moreover, this study focuses on studying the temporal variability of the Z-R relation for Mediterranean areas. The radar device is provided with an automatic operational ground-clutter filter developed by the producer. Attention has been paid to the development of blending procedures between radar measurements and other auxiliary instruments and to their suitability for both meteorological and hydrological applications. A general scheme enveloping these procedures and achieving the combination of data retrieved from the weather radar, the optical disdrometer, and the rain gauge network distributed within the monitored area has been designed. The first step of the procedure consists in the calibration of the radar equation by comparing the match between the radar raw data and the disdrometer reflectivity. The second step is the calibration of the Z-R relationship based on the retrieval of parameters that optimize the transformation of disdrometer reflectivity into rainfall intensity, starting from the disdrometer rainfall intensity measurements. The Z-R calibration has been applied to the disdrometer measurements retrieved during a 1 year observation period, after a preliminary segmentation into separated rainfall events. This analysis allows for the characterization of the variability of the Z-R relationship from event to event, deriving some considerations about its predictability as well. Results obtained from this analysis provide a geographical specific record, for the Mediterranean area, for the study of the spatial variability of the Z-R relationship. Finally, the set of operational procedures also includes a correction procedure of radar estimates based on rain gauge data. Each

  7. Investigation of Advanced Radar Techniques for Atmospheric Hazard Detection with Airborne Weather Radar

    NASA Technical Reports Server (NTRS)

    Pazmany, Andrew L.

    2014-01-01

    In 2013 ProSensing Inc. conducted a study to investigate the hazard detection potential of aircraft weather radars with new measurement capabilities, such as multi-frequency, polarimetric and radiometric modes. Various radar designs and features were evaluated for sensitivity, measurement range and for detecting and quantifying atmospheric hazards in wide range of weather conditions. Projected size, weight, power consumption and cost of the various designs were also considered. Various cloud and precipitation conditions were modeled and used to conduct an analytic evaluation of the design options. This report provides an overview of the study and summarizes the conclusions and recommendations.

  8. Beam Propagator for Weather Radars, Modules 1 and 2

    Energy Science and Technology Software Center (ESTSC)

    2013-10-08

    This program simulates the beam propagation of weather radar pulses under particular and realistic atmospheric conditions (without using the assumption of standard refraction conditions). It consists of two modules: radiosondings_refract_index_many.pro (MAIN MODULE) beam_propagation_function.pro(EXTERNAL FUNCTION) FOR THE MAIN MODULE, THE CODE DOES OUTPUT--INTO A FILE--THE BEAM HEIGHT AS A FUNCTION OF RANGE. THE RADIOSONDE INPUT FILES SHOULD BE ALREADY AVAILABLE BY THE USER. FOR EXAMPLE, RADIOSONDE OBSERVATION FILES CAN BE OBTAINED AT: RADIOSONDE OBSERVATIONS DOWNLOADED ATmore » "http://weather.uwyo.edu/upperair/soounding.html" OR "http://jervis.pyr.ec.gc.ca" THE EXTERNAL FUNCTION DOES THE ACTUAL COMPUTATION OF BEAM PROPAGATION. IT INCLUDES CONDITIONS OF ANOMALOUS PROPAGATION AND NEGATIVE ELEVATION ANGLES. THE EQUATIONS USED HERE WERE DERIVED BY EDWIN CAMPOS, BASED ON THE SNELL-DESCARTES LAW OF REFRACTION, CONSIDERING THE EARTH CURVATURE. THE PROGRAM REQUIRES A COMPILER FOR THE INTERACTIVE DATA LANGUAGE (IDL). DESCRIPTION AND VALIDATION DETAILS HAVE BEEN PUBLISHED IN THE PEER-REVIEWED SCIENTIFIC LITERATURE, AS FOLLOWS: Campos E. 2012. Estimating weather radar coverage over complex terrain, pp.26-32, peer reviewed, in Weather Radar and Hydrology, edited by Moore RJ, Cole SJ and Illingworth AJ. International Association of Hydrological Sciences (IAHS) Press, IAHS Publ. 351. ISBN 978-1-907161-26-1.« less

  9. Beam Propagator for Weather Radars, Modules 1 and 2

    SciTech Connect

    Ortega, Edwin Campos

    2013-10-08

    This program simulates the beam propagation of weather radar pulses under particular and realistic atmospheric conditions (without using the assumption of standard refraction conditions). It consists of two modules: radiosondings_refract_index_many.pro (MAIN MODULE) beam_propagation_function.pro(EXTERNAL FUNCTION) FOR THE MAIN MODULE, THE CODE DOES OUTPUT--INTO A FILE--THE BEAM HEIGHT AS A FUNCTION OF RANGE. THE RADIOSONDE INPUT FILES SHOULD BE ALREADY AVAILABLE BY THE USER. FOR EXAMPLE, RADIOSONDE OBSERVATION FILES CAN BE OBTAINED AT: RADIOSONDE OBSERVATIONS DOWNLOADED AT "http://weather.uwyo.edu/upperair/soounding.html" OR "http://jervis.pyr.ec.gc.ca" THE EXTERNAL FUNCTION DOES THE ACTUAL COMPUTATION OF BEAM PROPAGATION. IT INCLUDES CONDITIONS OF ANOMALOUS PROPAGATION AND NEGATIVE ELEVATION ANGLES. THE EQUATIONS USED HERE WERE DERIVED BY EDWIN CAMPOS, BASED ON THE SNELL-DESCARTES LAW OF REFRACTION, CONSIDERING THE EARTH CURVATURE. THE PROGRAM REQUIRES A COMPILER FOR THE INTERACTIVE DATA LANGUAGE (IDL). DESCRIPTION AND VALIDATION DETAILS HAVE BEEN PUBLISHED IN THE PEER-REVIEWED SCIENTIFIC LITERATURE, AS FOLLOWS: Campos E. 2012. Estimating weather radar coverage over complex terrain, pp.26-32, peer reviewed, in Weather Radar and Hydrology, edited by Moore RJ, Cole SJ and Illingworth AJ. International Association of Hydrological Sciences (IAHS) Press, IAHS Publ. 351. ISBN 978-1-907161-26-1.

  10. Application of the Doppler weather radar in real-time quality control of hourly gauge precipitation in eastern China

    NASA Astrophysics Data System (ADS)

    Zhong, Lingzhi; Zhang, Zhiqiang; Chen, Lin; Yang, Jinhong; Zou, Fengling

    2016-05-01

    The current real-time operational quality control method for hourly rain gauge records at meteorological stations of China is primarily based on a comparison with historical extreme records, and the spatial and temporal consistencies of rain records. However, this method might make erroneous judgments for heavy precipitation because of its remarkable inhomogeneous features. In this study, we develop a Radar Supported Operational Real-time Quality Control (RS_ORQC) method to improve hourly gauge precipitation records in eastern China by using Doppler weather radar data and national automatic rain-gauge network in JJA (i.e., June, July and August) between 2010 and 2011. According to the probability density function (PDF) and cumulative probability density function (CDF), we establish the statistic relationships between NSN precipitation records under 7 radar coverage and radar quantitative precipitation estimation (QPE). The other NSN records under 5 radar coverage are used for the verification. The results show that the correct rate of this radar-supported new method in judging gauge precipitation is close to 99.95% when the hourly rainfall rate is below 10 mm h- 1 and is 96.21% when the rainfall intensity is above 10 mm h- 1. Moreover, the improved quality control method is also applied to evaluate the quality of provincial station network (PSN) precipitation records over eastern China. The correct rate of PSN precipitation records is 99.92% when the hourly rainfall rate is below 10 mm h- 1, and it is 93.33% when the hourly rainfall rate is above 10 mm h- 1. Case studies also exhibit that the radar-supported method can make correct judgments for extreme heavy rainfall.

  11. A space-time geostatistical framework for ensemble nowcasting using rainfall radar fields and gauge data

    NASA Astrophysics Data System (ADS)

    Caseri, Angelica; Ramos, Maria Helena; Javelle, Pierre; Leblois, Etienne

    2016-04-01

    Floods are responsible for a major part of the total damage caused by natural disasters. Nowcasting systems providing public alerts to flash floods are very important to prevent damages from extreme events and reduce their socio-economic impacts. The major challenge of these systems is to capture high-risk situations in advance, with good accuracy in the intensity, location and timing of future intense precipitation events. Flash flood forecasting has been studied by several authors in different affected areas. The majority of the studies combines rain gauge data with radar imagery advection to improve prediction for the next few hours. Outputs of Numerical Weather Prediction (NWP) models have also been increasingly used to predict ensembles of extreme precipitation events that might trigger flash floods. One of the challenges of the use of NWP for ensemble nowcasting is to successfully generate ensemble forecasts of precipitation in a short time calculation period to enable the production of flood forecasts with sufficient advance to issue flash flood alerts. In this study, we investigate an alternative space-time geostatistical framework to generate multiple scenarios of future rainfall for flash floods nowcasting. The approach is based on conditional simulation and an advection method applied within the Turning Bands Method (TBM). Ensemble forecasts of precipitation fields are generated based on space-time properties given by radar images and precipitation data collected from rain gauges during the development of the rainfall event. The results show that the approach developed can be an interesting alternative to capture precipitation uncertainties in location and intensity and generate ensemble forecasts of rainfall that can be useful to improve alerts for flash floods, especially in small areas.

  12. Statistical model of the range-dependent error in radar-rainfall estimates due to the vertical profile of reflectivity

    NASA Astrophysics Data System (ADS)

    Krajewski, Witold F.; Vignal, Bertrand; Seo, Bong-Chul; Villarini, Gabriele

    2011-05-01

    SummaryThe authors developed an approach for deriving a statistical model of range-dependent error (RDE) in radar-rainfall estimates by parameterizing the structure of the non-uniform vertical profile of radar reflectivity (VPR). The proposed parameterization of the mean VPR and its expected variations are characterized by several climatological parameters that describe dominant atmospheric conditions related to vertical reflectivity variation. We have used four years of radar volume scan data from the Tulsa weather radar WSR-88D (Oklahoma) to illustrate this approach and have estimated the model parameters by minimizing the sum of the squared differences between the modeled and observed VPR influences that were computed using radar data. We evaluated the mean and standard deviation of the modeled RDE against rain gauge data from the Oklahoma Mesonet network. No rain gauge data were used in the model development. The authors used the three lowest antenna elevation angles to demonstrate the model performance for cold (November-April) and warm (May-October) seasons. The RDE derived from the parameterized models shows very good agreement with the observed differences between radar and rain gauge estimates of rainfall. For the third elevation angle and cold season, there are 82% and 42% improvements for the RDE and its standard deviation with respect to the no-VPR case. The results of this study indicate that VPR is a key factor in the characterization of the radar range-dependent bias, and the proposed models can be used to represent the radar RDE in the absence of rain gauge data.

  13. Radar rainfall estimation in the context of post-event analysis of flash-flood events

    NASA Astrophysics Data System (ADS)

    Bouilloud, Ludovic; Delrieu, Guy; Boudevillain, Brice; Kirstetter, Pierre-Emmanuel

    2010-11-01

    SummaryA method to estimate rainfall from radar data for post-event analysis of flash-flood events has been developed within the EC-funded HYDRATE project. It follows a pragmatic approach including careful analysis of the observation conditions for the radar system(s) available for the considered case. Clutter and beam blockage are characterised by dry-weather observations and simulations based on a digital terrain model of the region of interest. The vertical profile of reflectivity (VPR) is either inferred from radar data if volume scanning data are available or simply defined using basic meteorological parameters (idealised VPR). Such information is then used to produce correction factor maps for each elevation angle to correct for range-dependent errors. In a second step, an effective Z-R relationship is optimised to remove the bias over the hit region. Due to limited data availability, the optimisation is carried out with reference to raingauge rain amounts measured at the event time scale. Sensitivity tests performed with two well-documented rain events show that a number of Z = aRb relationships, organised along hyperbolic curves in the (a and b) parameter space, lead to optimum assessment results in terms of the Nash coefficient between the radar and raingauge estimates. A refined analysis of these equifinality patterns shows that the “total additive conditional bias” can be used to discriminate between the Nash coefficient equifinal solutions. We observe that the optimisation results are sensitive to the VPR description and also that the Z-R optimisation procedure can largely compensate for range-dependent errors, although this shifts the optimal coefficients in the parameter space. The time-scale dependency of the equifinality patterns is significant, however near-optimal Z-R relationships can be obtained at all time scales from the event time step optimisation.

  14. Multiparameter radar study of rainfall: Potential application to area-time integral studies

    NASA Technical Reports Server (NTRS)

    Raghavan, R.; Chandrasekar, V.

    1994-01-01

    Multiparameter radars measure one or more additional parameters in addition to the coventional reflectivity factor. The combination of radar observations from a multiparameter radar is used to study the time evolution of rainstorms. A technique is presented to self-consistently compare the area-time integral (ATI) and rainfall volume estimates from convective storms, using two different measurements from a multiparameter radar. Rainfall volumes for the lifetime of individual storms are computed using the reflectivity at S band (10-cm wavelength) as well as one-way specific attenuation at X band (3-cm wavelength). Area-time integrals are computed by summing all areas in each radar snapshot having reflectivities (S band) in excess of a preselected threshold. The multiparameter radar data used in this study were acquired by the National Center for Atmospheric Research (NCAR) CP-2 radar during the Cooperative Huntsville Meteorological Experiment (COHMEX) and the Convection and Precipitation/Electrification Experiment (CaPE), respectively. ATI studies were accomplished in this work using multiparameter radar data acquired during the lifetime of six convective events that occurred in the COHMEX radar coverage area. A case study from the COMHEX field campaign (20 July 1986) was selected to depict the various stages in the evolution of a storm over which the ATI and rainfall volume computations were performed using multiparameter radar data. Another case study from the CaPE field campaign (12 August 1991) was used to demonstrate the evolution of a convective cell based on differential reflectivity observations.

  15. Rainfall estimation by rain gauge-radar combination: A concurrent multiplicative-additive approach

    NASA Astrophysics Data System (ADS)

    GarcíA-Pintado, Javier; Barberá, Gonzalo G.; Erena, Manuel; Castillo, Victor M.

    2009-01-01

    A procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) is proposed for operational rainfall estimation using rain gauges and radar data. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on Barnes' objective analysis scheme (OAS), whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, a spatially variable adjustment with multiplicative factors, and ordinary cokriging.

  16. Predictability of heavy sub-hourly precipitation amounts for a weather radar based nowcasting system

    NASA Astrophysics Data System (ADS)

    Bech, Joan; Berenguer, Marc

    2015-04-01

    Heavy precipitation events and subsequent flash floods are one of the most dramatic hazards in many regions such as the Mediterranean basin as recently stressed in the HyMeX (HYdrological cycle in the Mediterranean EXperiment) international programme. The focus of this study is to assess the quality of very short range (below 3 hour lead times) precipitation forecasts based on weather radar nowcasting system. Specific nowcasting amounts of 10 and 30 minutes generated with a nowcasting technique (Berenguer et al 2005, 2011) are compared against raingauge observations and also weather radar precipitation estimates observed over Catalonia (NE Spain) using data from the Meteorological Service of Catalonia and the Water Catalan Agency. Results allow to discuss the feasibility of issuing warnings for different precipitation amounts and lead times for a number of case studies, including very intense convective events with 30minute precipitation amounts exceeding 40 mm (Bech et al 2005, 2011). As indicated by a number of verification scores single based radar precipitation nowcasts decrease their skill quickly with increasing lead times and rainfall thresholds. This work has been done in the framework of the Hymex research programme and has been partly funded by the ProFEWS project (CGL2010-15892). References Bech J, N Pineda, T Rigo, M Aran, J Amaro, M Gayà, J Arús, J Montanyà, O van der Velde, 2011: A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis. Atmospheric Research 100:621-637 http://dx.doi.org/10.1016/j.atmosres.2010.12.024 Bech J, R Pascual, T Rigo, N Pineda, JM López, J Arús, and M Gayà, 2007: An observational study of the 7 September 2005 Barcelona tornado outbreak. Natural Hazards and Earth System Science 7:129-139 http://dx.doi.org/10.5194/nhess-7-129-2007 Berenguer M, C Corral, R Sa0nchez-Diezma, D Sempere-Torres, 2005: Hydrological validation of a radar based nowcasting technique. Journal of

  17. Development of High Altitude UAV Weather Radars for Hurricane Research

    NASA Technical Reports Server (NTRS)

    Heymsfield, Gerald; Li, Li-Hua

    2005-01-01

    A proposed effort within NASA called (ASHE) over the past few years was aimed at studying the genesis of tropical disturbances off the east coast of Africa. This effort was focused on using an instrumented Global Hawk UAV with high altitude (%Ok ft) and long duration (30 h) capability. While the Global Hawk availability remains uncertain, development of two relevant instruments, a Doppler radar (URAD - UAV Radar) and a backscatter lidar (CPL-UAV - Cloud Physics Lidar), are in progress. The radar to be discussed here is based on two previous high-altitude, autonomously operating radars on the NASA ER-2 aircraft, the ER-2 Doppler Radar (EDOP) at X-band (9.6 GHz), and the Cloud Radar System (CRS) at W- band (94 GHz). The nadir-pointing EDOP and CRS radars profile vertical reflectivity structure and vertical Doppler winds in precipitation and clouds, respectively. EDOP has flown in all of the CAMEX flight series to study hurricanes over storms such as Hurricanes Bonnie, Humberto, Georges, Erin, and TS Chantal. These radars were developed at Goddard over the last decade and have been used for satellite algorithm development and validation (TRMM and Cloudsat), and for hurricane and convective storm research. We describe here the development of URAD that will measure wind and reflectivity in hurricanes and other weather systems from a top down, high-altitude view. URAD for the Global Hawk consists of two subsystems both of which are at X-band (9.3-9.6 GHz) and Doppler: a nadir fixed-beam Doppler radar for vertical motion and precipitation measurement, and a Conical scanning radar for horizontal winds in cloud and at the surface, and precipitation structure. These radars are being designed with size, weight, and power consumption suitable for the Global Hawk and other UAV's. The nadir radar uses a magnetron transmitter and the scanning radar uses a TWT transmitter. With conical scanning of the radar at a 35" incidence angle over an ocean surface in the absence of

  18. Application of bias correction methods to improve the accuracy of quantitative radar rainfall in Korea

    NASA Astrophysics Data System (ADS)

    Lee, J.-K.; Kim, J.-H.; Suk, M.-K.

    2015-11-01

    There are many potential sources of the biases in the radar rainfall estimation process. This study classified the biases from the rainfall estimation process into the reflectivity measurement bias and the rainfall estimation bias by the Quantitative Precipitation Estimation (QPE) model and also conducted the bias correction methods to improve the accuracy of the Radar-AWS Rainrate (RAR) calculation system operated by the Korea Meteorological Administration (KMA). In the Z bias correction for the reflectivity biases occurred by measuring the rainfalls, this study utilized the bias correction algorithm. The concept of this algorithm is that the reflectivity of the target single-pol radars is corrected based on the reference dual-pol radar corrected in the hardware and software bias. This study, and then, dealt with two post-process methods, the Mean Field Bias Correction (MFBC) method and the Local Gauge Correction method (LGC), to correct the rainfall estimation bias by the QPE model. The Z bias and rainfall estimation bias correction methods were applied to the RAR system. The accuracy of the RAR system was improved after correcting Z bias. For the rainfall types, although the accuracy of the Changma front and the local torrential cases was slightly improved without the Z bias correction the accuracy of the typhoon cases got worse than the existing results in particular. As a result of the rainfall estimation bias correction, the Z bias_LGC was especially superior to the MFBC method because the different rainfall biases were applied to each grid rainfall amount in the LGC method. For the rainfall types, the results of the Z bias_LGC showed that the rainfall estimates for all types was more accurate than only the Z bias and, especially, the outcomes in the typhoon cases was vastly superior to the others.

  19. An operational approach for classifying storms in real-time radar rainfall estimation

    NASA Astrophysics Data System (ADS)

    Chumchean, Siriluk; Seed, Alan; Sharma, Ashish

    2008-12-01

    SummaryThis paper presents an operational approach to integrate a storm classification method into a real-time radar rainfall estimation. A minor modification of a texturing classification algorithm proposed by Steiner et al. [Steiner, M., Houze Jr., R.A., Yuter, S.E., 1995. Climatological characterisation of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteorol. 34, 1978-2007] that can classify each pixel in the radar image as stratiform or convective is used to classify the instantaneous reflectivity field into convective and stratiform components. A method to derive the climatological Z-R relations for convective and stratiform rainfall is proposed. Vertical profiles of reflectivity (VPRs) are used to verify the accuracy of the storm classification. An alternative method for verification of a storm classification scheme based on differences between probability distribution functions of rain gauge rainfall of the two rainfall categories is also presented. A 6-month record of radar and rain gauge rainfall for Sydney, Australia for November 2000-April 2001 is used for training and rainfall events during February 2007-March 2007 are used to evaluate the efficiency and applicability of the proposed methods. The results show that the proposed operational approach for classifying storms in real-time radar rainfall estimates reduces RMSE between radar and rain gauge rainfall from 4.63 to 4.30 mm h -1 and from 5.31 to 5.01 mm h -1 for the training and verification periods compared to the case where the rainfall is assumed to have a single Z-R relationship.

  20. Image processing for hazard recognition in on-board weather radar

    NASA Technical Reports Server (NTRS)

    Kelly, Wallace E. (Inventor); Rand, Timothy W. (Inventor); Uckun, Serdar (Inventor); Ruokangas, Corinne C. (Inventor)

    2003-01-01

    A method of providing weather radar images to a user includes obtaining radar image data corresponding to a weather radar image to be displayed. The radar image data is image processed to identify a feature of the weather radar image which is potentially indicative of a hazardous weather condition. The weather radar image is displayed to the user along with a notification of the existence of the feature which is potentially indicative of the hazardous weather condition. Notification can take the form of textual information regarding the feature, including feature type and proximity information. Notification can also take the form of visually highlighting the feature, for example by forming a visual border around the feature. Other forms of notification can also be used.

  1. Approaches to radar reflectivity bias correction to improve rainfall estimation in Korea

    NASA Astrophysics Data System (ADS)

    You, Cheol-Hwan; Kang, Mi-Young; Lee, Dong-In; Lee, Jung-Tae

    2016-05-01

    Three methods for determining the reflectivity bias of single polarization radar using dual polarization radar reflectivity and disdrometer data (i.e., the equidistance line, overlapping area, and disdrometer methods) are proposed and evaluated for two low-pressure rainfall events that occurred over the Korean Peninsula on 25 August 2014 and 8 September 2012. Single polarization radar reflectivity was underestimated by more than 12 and 7 dB in the two rain events, respectively. All methods improved the accuracy of rainfall estimation, except for one case where drop size distributions were not observed, as the precipitation system did not pass through the disdrometer location. The use of these bias correction methods reduced the RMSE by as much as 50 %. Overall, the most accurate rainfall estimates were obtained using the overlapping area method to correct radar reflectivity.

  2. Attenuation of Weather Radar Signals Due to Wetting of the Radome by Rainwater or Incomplete Filling of the Beam Volume

    NASA Technical Reports Server (NTRS)

    Merceret, Francis J.; Ward, Jennifer G.

    2000-01-01

    A search of scientific literature, both printed and electronic, was undertaken to provide quantitative estimates of attenuation effects of rainfall on weather radar radomes. The emphasis was on C-band (5 cm) and S-Band (10 cm) wavelengths. An empirical model was developed to estimate two-way wet radome losses as a function of frequency and rainfall rate for both standard and hydrophobic radomes. The model fits most of the published data within +/- 1 dB at both target wavelengths for rain rates from less than ten to more than 200 mm/hr. Rainfall attenuation effects remain under 1 dB at both frequencies regardless of radome type for rainfall rates up to 10 mm/hr. S-Band losses with a hydrophobic radome such as that on the WSR-88D remain under 1 dB up to 100 mm/hr. C-Band losses on standard radomes such as that on the Patrick AFB (Air Force Base) WSR-74C can reach as much as 5 dB at 50 mm/hr. In addition, calculations were performed to determine the reduction in effective reflectivity, Z, when a radar target is smaller than the sampling volume of the radar. Results are presented for both the Patrick Air Force Base WSR-74C and the WSR-88D as a function of target size and range.

  3. Post Processing Numerical Weather Prediction Model Rainfall Forecasts for Use in Ensemble Streamflow Forecasting in Australia

    NASA Astrophysics Data System (ADS)

    Shrestha, D. L.; Robertson, D.; Bennett, J.; Ward, P.; Wang, Q. J.

    2012-12-01

    Through the water information research and development alliance (WIRADA) project, CSIRO is conducting research to improve flood and short-term streamflow forecasting services delivered by the Australian Bureau of Meteorology. WIRADA aims to build and test systems to generate ensemble flood and short-term streamflow forecasts with lead times of up to 10 days by integrating rainfall forecasts from Numerical Weather Prediction (NWP) models and hydrological modelling. Here we present an overview of the latest progress towards developing this system. Rainfall during the forecast period is a major source of uncertainty in streamflow forecasting. Ensemble rainfall forecasts are used in streamflow forecasting to characterise the rainfall uncertainty. In Australia, NWP models provide forecasts of rainfall and other weather conditions for lead times of up to 10 days. However, rainfall forecasts from Australian NWP models are deterministic and often contain systematic errors. We use a simplified Bayesian joint probability (BJP) method to post-process rainfall forecasts from the latest generation of Australian NWP models. The BJP method generates reliable and skilful ensemble rainfall forecasts. The post-processed rainfall ensembles are then used to force a semi-distributed conceptual rainfall runoff model to produce ensemble streamflow forecasts. The performance of the ensemble streamflow forecasts is evaluated on a number of Australian catchments and the benefits of using post processed rainfall forecasts are demonstrated.

  4. Prediction of a Flash Flood in Complex Terrain. Part I: A Comparison of Rainfall Estimates from Radar, and Very Short Range Rainfall Simulations from a Dynamic Model and an Automated Algorithmic System.

    NASA Astrophysics Data System (ADS)

    Warner, Thomas T.; Brandes, Edward A.; Sun, Juanzhen; Yates, David N.; Mueller, Cynthia K.

    2000-06-01

    Operational prediction of flash floods caused by convective rainfall in mountainous areas requires accurate estimates or predictions of the rainfall distribution in space and time. The details of the spatial distribution are especially critical in complex terrain because the watersheds generally are small in size, and position errors in the placement of the rainfall can distribute the rain over the wrong watershed. In addition to the need for good rainfall estimates, accurate flood prediction requires a surface-hydrologic model that is capable of predicting stream or river discharge based on the rainfall-rate input data. In part 1 of this study, different techniques for the estimation and prediction of convective rainfall are applied to the Buffalo Creek, Colorado, flash flood of July 1996, during which over 75 mm of rain from a thunderstorm fell on the watershed in less than 1 h. The hydrologic impact of the rainfall was exacerbated by the fact that a considerable fraction of the watershed experienced a wildfire approximately two months prior to the rain event.Precipitation estimates from the National Weather Service Weather Surveillance Radar-1988 Doppler and the National Center for Atmospheric Research S-band, dual-polarization radar, collocated east of Denver, Colorado, were compared. Very short range simulations from a convection-resolving dynamic model that was initialized variationally using the radar reflectivity and Doppler winds were compared with simulations from an automated algorithmic forecast system that also employs the radar data. The radar estimates of rain rate and the two forecasting systems that employ the radar data have degraded accuracy by virtue of the fact that they are applied in complex terrain. Nevertheless, the dynamic model and automated algorithms both produce simulations that could be useful operationally for input to surface-hydrologic models employed for flood warning. Part 2 of this study, reported in a companion paper, describes

  5. Winter precipitation fields in the Southeastern Mediterranean area as seen by the Ku-band spaceborne weather radar and two C-band ground-based radars

    NASA Astrophysics Data System (ADS)

    Gabella, M.; Morin, E.; Notarpietro, R.; Michaelides, S.

    2013-01-01

    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 8 dB 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 6 dB 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.

  6. wradlib - an Open Source Library for Weather Radar Data Processing

    NASA Astrophysics Data System (ADS)

    Pfaff, Thomas; Heistermann, Maik; Jacobi, Stephan

    2014-05-01

    Even though weather radar holds great promise for the hydrological sciences, offering precipitation estimates with unrivaled spatial and temporal resolution, there are still problems impeding its widespread use, among which are: almost every radar data set comes with a different data format with public reading software being available only rarely. standard products as issued by the meteorological services often do not serve the needs of original research, having either too many or too few corrections applied. Especially when new correction methods are to be developed, researchers are often forced to start from scratch having to implement many corrections in addition to those they are actually interested in. many algorithms published in the literature cannot be recreated using the corresponding article only. Public codes, providing insight into the actual implementation and how an approach deals with possible exceptions are rare. the radial scanning setup of weather radar measurements produces additional challenges, when it comes to visualization or georeferencing of this type of data. Based on these experiences, and in the hope to spare others at least some of these tedious tasks, wradlib offers the results of the author's own efforts and a growing number of community-supplied methods. wradlib is designed as a Python library of functions and classes to assist users in their analysis of weather radar data. It provides solutions for all tasks along a typical processing chain leading from raw reflectivity data to corrected, georeferenced and possibly gauge adjusted quantitative precipitation estimates. There are modules for data input/output, data transformation including Z/R transformation, clutter identification, attenuation correction, dual polarization and differential phase processing, interpolation, georeferencing, compositing, gauge adjustment, verification and visualization. The interpreted nature of the Python programming language makes wradlib an ideal tool

  7. Bird migration flight altitudes studied by a network of operational weather radars.

    PubMed

    Dokter, Adriaan M; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

    2011-01-01

    A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which--when extended to multiple radars--enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe. PMID:20519212

  8. Dual-parameter radar rainfall measurement from space - A test result from an aircraft experiment

    NASA Technical Reports Server (NTRS)

    Kozu, Toshiaki; Nakamura, Kenji; Meneghini, Robert; Boncyk, Wayne C.

    1991-01-01

    An aircraft experiment has been conducted with a dual-frequency (X/Ka-bands) radar to test various rainfall retrieval methods from space. The authors test a method to derive raindrop size distribution (DSD) parameters from the combination of a radar reflectivity profile and a path-integrated attenuation derived from surface return, which may be available from most spaceborne radars. The estimated DSD parameters are reasonable in that the values generally fall within the range of commonly measured ones and that shifts in DSD parameters appear to be correlated with changes in storm type. The validity of the estimation result is also demonstrated by a consistency check using the Ka-band reflectivity profile which is independent of the DSD estimation process. Although errors may occur in the cases of nonuniform beam filling, these test results indicate the feasibility of the dual-parameter radar measurement from space in achieving a better accuracy in quantitative rainfall remote measurements.

  9. Improving radar estimates of rainfall using an input subset of artificial neural networks

    NASA Astrophysics Data System (ADS)

    Yang, Tsun-Hua; Feng, Lei; Chang, Lung-Yao

    2016-04-01

    An input subset including average radar reflectivity (Zave) and its standard deviation (SD) is proposed to improve radar estimates of rainfall based on a radial basis function (RBF) neural network. The RBF derives a relationship from a historical input subset, called a training dataset, consisting of radar measurements such as reflectivity (Z) aloft and associated rainfall observation (R) on the ground. The unknown rainfall rate can then be predicted over the derived relationship with known radar measurements. The selection of the input subset has a significant impact on the prediction performance. This study simplified the selection of input subsets and studied its improvement in rainfall estimation. The proposed subset includes: (1) the Zave of the observed Z within a given distance from the ground observation to represent the intensity of a storm system and (2) the SD of the observed Z to describe the spatial variability. Using three historical rainfall events in 1999 near Darwin, Australia, the performance evaluation is conducted using three approaches: an empirical Z-R relation, RBF with Z, and RBF with Zave and SD. The results showed that the RBF with both Zave and SD achieved better rainfall estimations than the RBF using only Z. Two performance measures were used: (1) the Pearson correlation coefficient improved from 0.15 to 0.58 and (2) the average root-mean-square error decreased from 14.14 mm to 11.43 mm. The proposed model and findings can be used for further applications involving the use of neural networks for radar estimates of rainfall.

  10. Advanced Precipitation Radar Antenna to Measure Rainfall From Space

    NASA Technical Reports Server (NTRS)

    Rahmat-Samii, Yahya; Lin, John; Huang, John; Im, Eastwood; Lou, Michael; Lopez, Bernardo; Durden, Stephen

    2008-01-01

    To support NASA s planned 20-year mission to provide sustained global precipitation measurement (EOS-9 Global Precipitation Measurement (GPM)), a deployable antenna has been explored with an inflatable thin-membrane structure. This design uses a 5.3 5.3-m inflatable parabolic reflector with the electronically scanned, dual-frequency phased array feeds to provide improved rainfall measurements at 2.0-km horizontal resolution over a cross-track scan range of up to 37 , necessary for resolving intense, isolated storm cells and for reducing the beam-filling and spatial sampling errors. The two matched radar beams at the two frequencies (Ku and Ka bands) will allow unambiguous retrieval of the parameters in raindrop size distribution. The antenna is inflatable, using rigidizable booms, deployable chain-link supports with prescribed curvatures, a smooth, thin-membrane reflecting surface, and an offset feed technique to achieve the precision surface tolerance (0.2 mm RMS) for meeting the low-sidelobe requirement. The cylindrical parabolic offset-feed reflector augmented with two linear phased array feeds achieves dual-frequency shared-aperture with wide-angle beam scanning and very low sidelobe level of -30 dB. Very long Ku and Ka band microstrip feed arrays incorporating a combination of parallel and series power divider lines with cosine-over-pedestal distribution also augment the sidelobe level and beam scan. This design reduces antenna mass and launch vehicle stowage volume. The Ku and Ka band feed arrays are needed to achieve the required cross-track beam scanning. To demonstrate the inflatable cylindrical reflector with two linear polarizations (V and H), and two beam directions (0deg and 30deg), each frequency band has four individual microstrip array designs. The Ku-band array has a total of 166x2 elements and the Ka-band has 166x4 elements with both bands having element spacing about 0.65 lambda(sub 0). The cylindrical reflector with offset linear array feeds

  11. Effects of Nonuniform Beam Filling on Rainfall Retrieval for the TRMM Precipitation Radar

    NASA Technical Reports Server (NTRS)

    Durden, Stephen L.; Haddad, Z. S.; Kitiyakara, A.; Li, F. K.

    1998-01-01

    The Tropical Rainfall Measuring Mission (TRMM) will carry the first spaceborne radar for rainfall observation. Because the TRMM Precipitation Radar (PR) footprint size of 4.3 km is greater than the scale of some convective rainfall events, there is concern that nonuniform filling of the PR antenna beam may bias the retrieved rain-rate profile. The authors investigate this effect theoretically and then observationally using data from the NASA Jet Propulsion Laboratory Airborne Rain Mapping Radar (ARMAR), acquired during Tropical Oceans Global Atmosphere Coupled Ocean Atmosphere Response Experiment in early 1993. The authors' observational approach is to simulate TRMM PR data using the ARMAR data and compare the radar observables and retrieved rain rate from the simulated PR data with those corresponding to the high-resolution radar measurements. The authors find that the path-integrated attenuation and the resulting path-averaged rain rate are underestimated. The reflectivity and rain rate near the top of the rainfall column are overestimated. The near-surface reflectivity can be overestimated or underestimated, with a mean error very close to zero. The near-surface rain rate, however, is usually underestimated, sometimes severely.

  12. Development of Weather Radar Mosaic Products in the U.S. National Weather Service

    NASA Astrophysics Data System (ADS)

    Kitzmiller, D. H.; Guan, S.; Mello, C.; Dai, J.

    2002-05-01

    The Weather Surveillance Radar 1988 (Doppler) (WSR-88D) network contains 142 units within the conterminous United States, 7 units in Alaska, and 4 units in Hawaii. The units are maintained by several agencies of the federal government, including the National Weather Service, the Federal Aviation Administration, and the Department of Defense. Many users of the data require access to observations from multiple radars simultaneously, and various mechanisms have beendevised to create national- and regional-scale geographic composites. Within the National Weather Service, creation of mosaics at local forecast offices can take up a substantial portion of available computing resources. The Meteorological Development Laboratory has undertaken the development of a system that will centrally produce and disseminate a set of mosaic products covering the conterminous United States, thus reducing the need for local production of the products. The effort has been made possible by the recent completion of communications network upgrades that permit rapid central collection of data from all sites within the WSR-88D network. A review of the radar product suite will be presented. The suite presently includes reflectivity, precipitation ccumulation estimates, vertically-integrated liquid water estimates, 18-dBZ echo top heights, and convective storm cell information such as hail indications and Doppler indications of mesocyclones and tornadoes. The operational goal is the production of mosaics at approximately 2-km spatial resolution for reflectivity and 4-km resolution for other fields, on a 5-minute update cycle. Some products are currently made available in graphical format via the World-Wide Web. Substantial progress has been made in developing an automated procedure to identify nonprecipitation echoes, including birds, insects, ground clutter, and anomalous propagation. Tests comparing the outcome of automated target identification with manual identification will be presented.

  13. Effects of Multiple Scattering for Millimeter-Wavelength Weather Radars

    NASA Technical Reports Server (NTRS)

    Kobayashi, Satoru; Tanelli, Simone; Im, Eastwood

    2004-01-01

    Effects of multiple scattering on the reflectivity measurement for millimeter-wavelength weather radars are studied, in which backscattering enhancement may play an important role. In the previous works, the backscattering enhancement has been studied for plane wave injection, the reflection of which is received at the infinite distance. In this paper, a finite beam width of a Gaussian antenna pattern along with spherical wave is taken into account. A time-independent second order theory is derived for a single layer of clouds of a uniform density. The ordinary second-order scattering (ladder term) and the second-order backscattering enhancement (cross term) are derived for both the copolarized and cross-polarized waves.

  14. The MST radar technique: Requirements for operational weather forecasting

    NASA Technical Reports Server (NTRS)

    Larsen, M. F.

    1983-01-01

    There is a feeling that the accuracy of mesoscale forecasts for spatial scales of less than 1000 km and time scales of less than 12 hours can be improved significantly if resources are applied to the problem in an intensive effort over the next decade. Since the most dangerous and damaging types of weather occur at these scales, there are major advantages to be gained if such a program is successful. The interest in improving short term forecasting is evident. The technology at the present time is sufficiently developed, both in terms of new observing systems and the computing power to handle the observations, to warrant an intensive effort to improve stormscale forecasting. An assessment of the extent to which the so-called MST radar technique fulfills the requirements for an operational mesoscale observing network is reviewed and the extent to which improvements in various types of forecasting could be expected if such a network is put into operation are delineated.

  15. Bird migration flight altitudes studied by a network of operational weather radars

    PubMed Central

    Dokter, Adriaan M.; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan

    2011-01-01

    A fully automated method for the detection and quantification of bird migration was developed for operational C-band weather radar, measuring bird density, speed and direction as a function of altitude. These weather radar bird observations have been validated with data from a high-accuracy dedicated bird radar, which was stationed in the measurement volume of weather radar sites in The Netherlands, Belgium and France for a full migration season during autumn 2007 and spring 2008. We show that weather radar can extract near real-time bird density altitude profiles that closely correspond to the density profiles measured by dedicated bird radar. Doppler weather radar can thus be used as a reliable sensor for quantifying bird densities aloft in an operational setting, which—when extended to multiple radars—enables the mapping and continuous monitoring of bird migration flyways. By applying the automated method to a network of weather radars, we observed how mesoscale variability in weather conditions structured the timing and altitude profile of bird migration within single nights. Bird density altitude profiles were observed that consisted of multiple layers, which could be explained from the distinct wind conditions at different take-off sites. Consistently lower bird densities are recorded in The Netherlands compared with sites in France and eastern Belgium, which reveals some of the spatial extent of the dominant Scandinavian flyway over continental Europe. PMID:20519212

  16. Evaluating storm-scale groundwater recharge dynamics with coupled weather radar data and unsaturated zone modeling

    NASA Astrophysics Data System (ADS)

    Nasta, P.; Gates, J. B.; Lock, N.; Houston, A. L.

    2013-12-01

    Groundwater recharge rates through the unsaturated zone emerge from complex interactions within the soil-vegetation-atmosphere system that derive from nonlinear relationships amongst atmospheric boundary conditions, plant water use and soil hydraulic properties. While it is widely recognized that hydrologic models must capture soil water dynamics in order to provide reliable recharge estimates, information on episodic recharge generation remains uncommon, and links between storm-scale weather patterns and their influence on recharge is largely unexplored. In this study, the water balance of a heterogeneous one-dimensional soil domain (3 m deep) beneath a typical rainfed corn agro-ecosystem in eastern Nebraska was numerically simulated in HYDRUS-1D for 12 years (2001-2012) on hourly time steps in order to assess the relationships between weather events and episodic recharge generation. WSR-88D weather radar reflectivity data provided both rainfall forcing data (after estimating rain rates using the z/r ratio method) and a means of storm classification on a scale from convective to stratiform using storm boundary characteristics. Individual storm event importance to cumulative recharge generation was assessed through iterative scenario modeling (773 total simulations). Annual cumulative recharge had a mean value of 9.19 cm/yr (about 12 % of cumulative rainfall) with coefficient of variation of 73%. Simulated recharge generation events occurred only in late winter and spring, with a peak in May (about 35% of total annual recharge). Recharge generation is observed primarily in late spring and early summer because of the combination of high residual soil moisture following a winter replenishment period, heavy convective storms, and low to moderate potential evapotranspiration rates. During the growing season, high rates of root water uptake cause rapid soil water depletion, and the concurrent high potential evapotranspiration and low soil moisture prevented recharge

  17. Observations of Heavy Rainfall in a Post Wildland Fire Area Using X-Band Polarimetric Radar

    NASA Astrophysics Data System (ADS)

    Cifelli, R.; Matrosov, S. Y.; Gochis, D. J.; Kennedy, P.; Moody, J. A.

    2011-12-01

    Polarimetric X-band radar systems have been used increasingly over the last decade for rainfall measurements. Since X-band radar systems are generally less costly, more mobile, and have narrower beam widths (for same antenna sizes) than those operating at lower frequencies (e.g., C and S-bands), they can be used for the "gap-filling" purposes for the areas when high resolution rainfall measurements are needed and existing operational radars systems lack adequate coverage and/or resolution for accurate quantitative precipitation estimation (QPE). The main drawback of X-band systems is attenuation of radar signals, which is significantly stronger compared to frequencies used by "traditional" precipitation radars operating at lower frequencies. The use of different correction schemes based on polarimetric data can, to a certain degree, overcome this drawback when attenuation does not cause total signal extinction. This presentation will focus on examining the use of high-resolution data from the NOAA Earth System Research Laboratory (ESRL) mobile X-band dual polarimetric radar for the purpose of estimating precipitation in a post-wildland fire area. The NOAA radar was deployed in the summer of 2011 to examine the impact of gap-fill radar on QPE and the resulting hydrologic response during heavy rain events in the Colorado Front Range in collaboration with colleagues from the National Center for Atmospheric Research (NCAR), Colorado State University (CSU), and the U.S. Geological Survey (USGS). A network of rain gauges installed by NCAR, the Denver Urban Drainage Flood Control District (UDFCD), and the USGS are used to compare with the radar estimates. Supplemental data from NEXRAD and the CSU-CHILL dual polarimetric radar are also used to compare with the NOAA X-band and rain gauges. It will be shown that rainfall rates and accumulations estimated from specific differential phase measurements (KDP) at X-band are in good agreement with the measurements from the gauge

  18. Spaceborne Doppler Radar Measurements of Rainfall: Correction of Errors Induced by Pointing Uncertainties

    NASA Technical Reports Server (NTRS)

    Tanelli, Simone; Im, Eastwood; Kobayashi, Satoru; Mascelloni, Roberto; Facheris, Luca

    2005-01-01

    In this paper a sea surface radar echo spectral analysis technique to correct for the rainfall velocity error caused by radar-pointing uncertainty is presented. The correction procedure is quite straightforward when the radar is observing a homogeneous rainfall field. When nonuniform beam filling (NUBF) occurs and attenuating frequencies are used, however, additional steps are necessary in order to correctly estimate the antenna-pointing direction. This new technique relies on the application of the combined frequency-time (CFT) algorithm to correct for uneven attenuation effects on the observed sea surface Doppler spectrum. The performance of this correction technique was evaluated by a Monte Carlo simulation of the Doppler precipitation radar backscatter from high-resolution 3D rain fields (either generated by a cloud resolving numerical model or retrieved from airborne radar measurements). The results show that the antenna-pointing-induced error can, indeed, be reduced by the proposed technique in order to achieve 1 m s(exp -1) accuracy on rainfall vertical velocity estimates.

  19. Correcting for wind drift in high resolution radar rainfall products: a feasibility study

    NASA Astrophysics Data System (ADS)

    Sandford, Caroline

    2015-12-01

    Increasing demands from emergency responders for accurate flood prediction, particularly in cities, have motivated consistent increases in the resolution of urban drainage models. Such models are now primarily limited by the accuracy and resolution of the initialising rainfall field. Surface rainfall estimates from radar, traditionally derived at scales of order 1 km, are now requested at grid lengths of 100 m to drive improvements in the outputs of these models. Deriving radar precipitation products on grids at the sub-kilometre scale introduces new requirements for the processing of reflectivity measurements into surface rainfall rates. A major source of uncertainty is the physical distance between the radar measurement and the surface onto which precipitation falls. Whilst adjustments to account for inhomogeneity in the vertical reflectivity profile have been extensively investigated, the effects of horizontal displacement have not. This paper discusses the issue of wind drift, first by outlining the need for correction, and then by evaluating the corrections available for impact at the required scale. One correction is detailed and its sensitivity evaluated with respect to the assumptions necessary in its derivation. These sensitivities are verified by trials on the Met Office operational radar processing system, where errors on wind drift displacement estimates are shown to be of order 1 km or more. This is significantly greater than the grid length desired by hydrological users. The paper therefore concludes by suggesting further research necessary to ensure the accuracy of radar precipitation estimates at sub-kilometre resolution.

  20. Direct measurement of the combined effects of lichen, rainfall, and temperature on silicate weathering

    SciTech Connect

    Brady, P.V.; Dorn, R.I.; Brazel, A.J.; Clark, J.; Moore, R.B.; Glidewell, T.

    1999-10-01

    A key uncertainty in models of the global carbonate-silicate cycle and long-term climate is the way that silicates weather under different climatologic conditions, and in the presence or absence of organic activity. Digital imaging of basalts in Hawaii resolves the coupling between temperature, rainfall, and weathering in the presence and absence of lichens. Activation energies for abiotic dissolution of plagioclase (23.1 {+-} 2.5 kcal/mol) and olivine (21.3 {+-} 2.7 kcal/mol) are similar to those measured in the laboratory, and are roughly double those measured from samples taken underneath lichen. Abiotic weathering rates appear to be proportional to rainfall. Dissolution of plagioclase and olivine underneath lichen is far more sensitive to rainfall.

  1. Direct measurement of the combined effects of lichen, rainfall, and temperature onsilicate weathering

    USGS Publications Warehouse

    Brady, P.V.; Dorn, R.I.; Brazel, A.J.; Clark, J.; Moore, R.B.; Glidewell, T.

    1999-01-01

    A key uncertainty in models of the global carbonate-silicate cycle and long-term climate is the way that silicates weather under different climatologic conditions, and in the presence or absence of organic activity. Digital imaging of basalts in Hawaii resolves the coupling between temperature, rainfall, and weathering in the presence and absence of lichens. Activation energies for abiotic dissolution of plagioclase (23.1 ?? 2.5 kcal/mol) and olivine (21.3 ?? 2.7 kcal/mol) are similar to those measured in the laboratory, and are roughly double those measured from samples taken underneath lichen. Abiotic weathering rates appear to be proportional to rainfall. Dissolution of plagioclase and olivine underneath lichen is far more sensitive to rainfall.

  2. Potential use of weather radar to study movements of wintering waterfowl

    USGS Publications Warehouse

    Randall, Lori A.; Diehl, Robert H.; Wilson, Barry C.; Barrow, Wylie C.; Jeske, Clinton W.

    2011-01-01

    To protect and restore wintering waterfowl habitat, managers require knowledge of routine wintering waterfowl movements and habitat use. During preliminary screening of Doppler weather radar data we observed biological movements consistent with routine foraging flights of wintering waterfowl known to occur near Lacassine National Wildlife Refuge (NWR), Louisiana. During the winters of 2004–2005 and 2005–2006, we conducted field surveys to identify the source of the radar echoes emanating from Lacassine NWR. We compared field data to weather radar reflectivity data. Spatial and temporal patterns consistent with foraging flight movements appeared in weather radar data on all dates of field surveys. Dabbling ducks were the dominant taxa flying within the radar beam during the foraging flight period. Using linear regression, we found a positive log-linear relationship between average radar reflectivity (Z) and number of birds detected over the study area (P r2 = 0.62, n = 40). Ground observations and the statistically significant relationship between radar data and field data confirm that Doppler weather radar recorded the foraging flights of dabbling ducks. Weather radars may be effective tools for wintering waterfowl management because they provide broad-scale views of both diurnal and nocturnal movements. In addition, an extensive data archive enables the study of wintering waterfowl response to habitat loss, agricultural practices, wetland restoration, and other research questions that require multiple years of data.

  3. Comparing two radar rainfall products with the help of Multifractal Analysis

    NASA Astrophysics Data System (ADS)

    Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Bompard, Philippe; Schertzer, Daniel

    2014-05-01

    Distributed rainfall radar data are commonly used in hydrology and increasingly used in urban hydrology. However radar validation and comparison still commonly relies on standard scores such as Nash-Sutcliffe coefficient, Correlation and Quadratic Error, which enable to grasp neither the underlying spatio-temporal structure of the studied rainfall field nor meaningful statistics, i.e. of order larger than two. We implement an innovative methodology that relies on Universal Multifractal (UM) to compare two operational radar products covering the Paris region. The UM framework has been extensively used to characterize and simulate geophysical fields extremely variable over a wide range of scales such as rainfall with the help of only three parameters, which are furthermore physically meaningful. Both Météo-France operational radar mosaic and the CALAMAR radar product use the same single polarization C-band radar data. However their QPE algorithms are different, as well as the calibration with rain gauges. Cartesian fields of final resolution 1 km in space and 5 min in time are used in this study. Three rainfall events that occurred in 2010 and 2011 are used, in order to quantify the quality of the adjustment process we add to this comparison a non-adjusted CALAMAR radar product. As a first step, we compare these radar products to the Val de Marne County network of 27 rain gauges distributed over a 245 Km2 area. Standard scores at various resolutions (5min, 15min, 30min and 1h) are computed. The Météo France radar product is better correlated with these rain gauges data than both CALAMAR products at 5min scale, but we observe the opposite when we increase the time scale. We also observe that the CALAMAR adjustment process improves the correlation with rain gauges. In a second step, both spatial (2D maps) and temporal (1D time series for each pixel) multifractal analyses are performed and the UM parameters computed. Preliminary results suggest that both products do

  4. Simulation of Tornado over Brahmanbaria on 22 March 2013 using Doppler Weather Radar and WRF Model

    NASA Astrophysics Data System (ADS)

    Das, M. K.; Chowdhury, M.; Das, S.

    2013-12-01

    A tornado accompanied with thunderstorm, rainfall and hailstorm affected Brahmanbaria of Bangladesh in the afternoon of 22 March 2013. The tornadic storms are studied based on field survey, ground and radar observations. Low level moisture influx by southerly flow from the Bay of Bengal coupled with upper level westerly jet stream causing intense instability and shear in the wind fields triggered a series of storms for the day. The exact time and locations of the storms are investigated by using the Agartala and Cox's Bazar Doppler Weather Radar (DWR). Subsequently, the storms are simulated by using the WRF-ARW model at 1 km horizontal resolution based on 6 hourly analyses and boundary conditions of NCEP-FNL. Among the typical characteristics of the storms, the CAPE, surface wind speed, flow patterns, T-Φ gram, rainfall, sea level pressure, vorticity and vertical velocity are studied. Results show that while there are differences of 2-3 hours between the observed and simulated time of the storms, the distances between observed and simulated locations of the storms are several tens of kilometers. The maximum CAPE was generally above 2400 J kg-1 in the case. The maximum intensity of surface wind speed simulated by the model was only 38 m sec-1. This seems to be underestimated. The highest vertical velocity (updraft) simulated by the model was 250 m sec-1 around 800-950 hPa. The updraft reached up to 150 hPa. It seems that the funnel vortex reached the ground, and might have passed some places a few meters above the surface. According to the Fujita Pearson scale, this tornado can be classified as F-2 with estimated wind speed of 50-70 ms-1. Keywords: Tornado, DWR, NCEP-FNL, T-Φ gram, CAPE.

  5. Quantitative estimation of Tropical Rainfall Mapping Mission precipitation radar signals from ground-based polarimetric radar observations

    NASA Astrophysics Data System (ADS)

    Bolen, Steven M.; Chandrasekar, V.

    2003-06-01

    The Tropical Rainfall Mapping Mission (TRMM) is the first mission dedicated to measuring rainfall from space using radar. The precipitation radar (PR) is one of several instruments aboard the TRMM satellite that is operating in a nearly circular orbit with nominal altitude of 350 km, inclination of 35°, and period of 91.5 min. The PR is a single-frequency Ku-band instrument that is designed to yield information about the vertical storm structure so as to gain insight into the intensity and distribution of rainfall. Attenuation effects on PR measurements, however, can be significant and as high as 10-15 dB. This can seriously impair the accuracy of rain rate retrieval algorithms derived from PR signal returns. Quantitative estimation of PR attenuation is made along the PR beam via ground-based polarimetric observations to validate attenuation correction procedures used by the PR. The reflectivity (Zh) at horizontal polarization and specific differential phase (Kdp) are found along the beam from S-band ground radar measurements, and theoretical modeling is used to determine the expected specific attenuation (k) along the space-Earth path at Ku-band frequency from these measurements. A theoretical k-Kdp relationship is determined for rain when Kdp ≥ 0.5°/km, and a power law relationship, k = a Zhb, is determined for light rain and other types of hydrometers encountered along the path. After alignment and resolution volume matching is made between ground and PR measurements, the two-way path-integrated attenuation (PIA) is calculated along the PR propagation path by integrating the specific attenuation along the path. The PR reflectivity derived after removing the PIA is also compared against ground radar observations.

  6. Quality-based generation of weather radar Cartesian products

    NASA Astrophysics Data System (ADS)

    Osrodka, K.; Szturc, J.

    2015-05-01

    Weather radar data volumes are commonly processed to obtain various 2-D Cartesian products based on the transfer from polar to Cartesian representations through a certain interpolation method. In this research an algorithm of the spatial interpolation of polar reflectivity data employing quality index data is applied to find the Cartesian reflectivity as plan position indicator products. On this basis, quality-based versions of standard algorithms for the generation of the following products have been developed: ETOP (echo top), MAX (maximum of reflectivity), and VIL (vertically integrated liquid water). Moreover, as an example of a higher-level product, a CONVECTION (detection of convection) has been defined as a specific combination of the above-listed standard products. A corresponding quality field is determined for each generated product, taking into account the quality of the pixels from which a given product was determined and how large a fraction of the investigated heights was scanned. Examples of such quality-based products are presented in the paper.

  7. Development of Research Quality Radar-Rainfall Datasets for Hydrologic Studies

    NASA Astrophysics Data System (ADS)

    Krajewski, W. F.; Ciach, G. J.; Gupta, V. K.; Furey, P.

    2002-12-01

    Although there is plethora of radar-rainfall data readily available, there is lack of well-documented research quality data sets over land. Two well-known and extensively studied oceanic radar-rainfall data sets are the GATE and TOGA COARE. Both are well-documented and provide high space and time resolution data. These data sets and the efforts that went into the product development are described in scientific literature. Over land the most popular data sets are the operational products generated by NOAA from the network of WSR-88D radars. Some products combine data from radars and rain gauges but leave out little information for an independent evaluation of the quality of the product. Other long-term data sets, such as the Mississippi River Basin five-year long data sets created under the auspices of the GCIP program are the results of trade-offs between feasibility and accuracy. Data sets developed for TRMM validation are limited to the tropics. Recognizing the need for high-resolution flexible radar data sets for use in hydrologic studies of flood generation mechanism, land-atmosphere-vegetation interactions, and scaling of rainfall processes, we are developing a system that will provide such data sets. The essential characteristics of the system are: (1) ability to effectively remove non-precipitation echo; (2) flexibility in specifying the algorithm that converts the observable (i.e. radar reflectivity) into the variable of interest, i.e. rainfall on the ground according to some specific criteria; and (3) ability to describe the main features of the product uncertainty. Our system, based on the WSR-88D level II reflectivity data will possess these characteristics. It is efficient enough to generate a large (one year or more) data set of rainfall products at the resolution limited only by the raw radar data. It incorporates the quality controlled rain gauge information via a calibration process. The calibration criteria allow trade-off between different error

  8. Analysis of the heavy rainfall from Typhoon Plum using Doppler Radar

    NASA Astrophysics Data System (ADS)

    Jin, W.; Qu, Y.

    2013-12-01

    Using reanalysis and observational data and Doppler radar data, the structure and characteristics of the synoptic and mesoscale meteorological background are analyzed for a heavy rainfall over Xiaoshipeng town of Yingkou City in Liaoning province, China. The results show that: (1) several synoptic scale patterns formed the background for the heavy rainfall: the Pacific subtropical high extended to the West; a strong tropical storm named "Plum" moved to the northwest after it had landed; Northwest jet transported a lot of the water vapor to Liaoning; the weak cold air of Baikal Lake moved to south along the ridge before the northwest flow impact to Liaoning. (2) the factors conducive to strong convective precipitation: the existence of a deep wet layer, a narrow CAPE zone and a relative weak vertical wind sheer. (3) there is nonstop generation of new mesoscale convective cells during the heavy rainfall. There exists a maximum wind zone of 24m/s in the lower layer and a strong radar echo with 35dBz above 5km. And the variation of the low level southwest jet is in step with the variation of rainfall amount. The cyclonic convergence of the warm wet air in the mid-low level is a factor triggering and strengthening convection. The nonstop generation of mesoscale convective cells and the water vapor transport from the low level southwest jet are pushing the rainfall radar echo to above 40dBz and lasting for more than 5 hours and are considered the direct cause of this heavy rainfall.

  9. Flood frequency analysis using radar rainfall fields and stochastic storm transposition

    NASA Astrophysics Data System (ADS)

    Wright, Daniel B.; Smith, James A.; Baeck, Mary Lynn

    2014-02-01

    Flooding is the product of complex interactions among spatially and temporally varying rainfall, heterogeneous land surface properties, and drainage network structure. Conventional approaches to flood frequency analysis rely on assumptions regarding these interactions across a range of scales. The impacts of these assumptions on flood risk estimates are poorly understood. In this study, we present an alternative flood frequency analysis framework based on stochastic storm transposition (SST). We use SST to synthesize long records of rainfall over the Charlotte, North Carolina, USA metropolitan area by "reshuffling" radar rainfall fields, within a probabilistic framework, from a 10 year (2001-2010) high-resolution (15 min, 1 km2) radar data set. We use these resampled fields to drive a physics-based distributed hydrologic model for a heavily urbanized watershed in Charlotte. The approach makes it possible to estimate discharge return periods for all points along the drainage network without the assumptions regarding rainfall structure and its interactions with watershed features that are required using conventional methods. We develop discharge estimates for return periods from 10 to 1000 years for a range of watershed scales up to 110 km2. SST reveals that flood risk in the larger subwatersheds is dominated by tropical storms, while organized thunderstorm systems dominate flood risk in the smaller subwatersheds. We contrast these analyses with examples of potential problems that can arise from conventional frequency analysis approaches. SST provides an approach for examining the spatial extent of flooding and for incorporating nonstationarities in rainfall or land use into flood risk estimates.

  10. Simulations of Dual-Frequency Radar Rainfall Retrievals

    NASA Astrophysics Data System (ADS)

    D'Adderio, Leo Pio; Tokay, Ali; Meneghini, Robert; Liao, Liang; Petersen, Walter A.; Porcù, Federico

    2016-04-01

    The retrieval of raindrop size distribution (DSD) is one of the key objectives of National Aeronautics and Space Administration (NASA) Global Precipitation Measurement (GPM) Mission. The dual-frequency precipitation radar (DPR) on board GPM core satellite is the primary resource for the retrieval of DSD. The DPR operates at Ku- and Ka-band and these frequencies have different sensitivities to the precipitation at the surface. Both frequencies are subject to the attenuation but at different magnitude. The high sensitivity of Ka-band measurements intends to detect solid and/or light liquid precipitation, while Ku-band frequency will be able to measure relatively higher intensity precipitation. The data from simultaneous Ka- and Ku-band measurements will allow a more accurate estimation of the DSD. The DSD retrieval algorithm uses three-parameter gamma distribution where mass weighted diameter (Dmass), normalized intercept parameter with respect to the liquid water content, and the shape parameter will be derived from dual-frequency radar measurements. A key problem is the retrieval of three unknown with two measurements. The simulation of the dual frequency ratio (DFR), using disdrometric data collected in different field campaigns of Ground Validation (GV) program of GPM mission, can cast light on this retrieval problem. Furthermore, the use of a third and/or different wavelength in the satellite measurements can be an added value to correctly retrieve both light and heavy rain. This study seeks relationship between the DFR and Dmass in different rain regimes. The DFR based both on Ka-/Ku-band and on frequencies other than Ka-/Ku-band is investigated. The dependence on the gamma distribution shape parameter, which is set to three in the DPR DSD retrieval algorithm, of the DFR-Dmass relationship is also analyzed.

  11. Enhancement of radar rainfall estimates for urban hydrology through optical flow temporal interpolation and Bayesian gauge-based adjustment

    NASA Astrophysics Data System (ADS)

    Wang, Li-Pen; Ochoa-Rodríguez, Susana; Van Assel, Johan; Pina, Rui Daniel; Pessemier, Mieke; Kroll, Stefan; Willems, Patrick; Onof, Christian

    2015-12-01

    Rainfall estimates of the highest possible accuracy and resolution are required for urban hydrological applications, given the small size and fast response which characterise urban catchments. While radar rainfall estimates have the advantage of well capturing the spatial structure of rainfall fields and its variation in time, the commonly available radar rainfall products (typically at ∼1 km/5-10 min resolution) may still fail to satisfy the accuracy and resolution - in particular temporal resolution - requirements of urban hydrology. A methodology is proposed in this paper, to produce higher temporal resolution, more accurate radar rainfall estimates, suitable for urban hydrological applications. The proposed methodology entails two main steps: (1) Temporal interpolation of radar images from the originally-available temporal resolutions (i.e. 5-10 min) to finer resolutions at which local rain gauge data are commonly available (i.e. 1-2 min). This is done using a novel interpolation technique, based upon the multi-scale variational optical flow technique, and which can well capture the small-scale rainfall structures relevant at urban scales. (2) Local and dynamic gauge-based adjustment of the higher temporal resolution radar rainfall estimates is performed afterwards, by means of the Bayesian data merging method. The proposed methodology is tested using as case study a total of 8 storm events observed in the Cranbrook (UK) and Herent (BE) urban catchments, for which radar rainfall estimates, local rain gauge and depth/flow records, as well as recently calibrated urban drainage models were available. The results suggest that the proposed methodology can provide significantly improved radar rainfall estimates and thereby generate more accurate runoff simulations at urban scales, over and above the benefits derived from the mere application of Bayesian merging at the original temporal resolution at which radar estimates are available. The benefits of the proposed

  12. On the potential use of radar-derived information in operational numerical weather prediction

    NASA Technical Reports Server (NTRS)

    Mcpherson, R. D.

    1986-01-01

    Estimates of requirements likely to be levied on a new observing system for mesoscale meteonology are given. Potential observing systems for mesoscale numerical weather prediction are discussed. Thermodynamic profiler radiometers, infrared radiometer atmospheric sounders, Doppler radar wind profilers and surveillance radar, and moisture profilers are among the instruments described.

  13. Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services

    NASA Astrophysics Data System (ADS)

    Angulo, I.; Grande, O.; Jenn, D.; Guerra, D.; de la Vega, D.

    2015-05-01

    The World Meteorological Organization (WMO) has repeatedly expressed concern over the increasing number of impact cases of wind turbine farms on weather radars. Current signal processing techniques to mitigate wind turbine clutter (WTC) are scarce, so the most practical approach to this issue is the assessment of the potential interference from a wind farm before it is installed. To do so, and in order to obtain a WTC reflectivity model, it is crucial to estimate the radar cross section (RCS) of the wind turbines to be built, which represents the power percentage of the radar signal that is backscattered to the radar receiver. For the proposed model, a representative scenario has been chosen in which both the weather radar and the wind farm are placed on clear areas; i.e., wind turbines are supposed to be illuminated only by the lowest elevation angles of the radar beam. This paper first characterizes the RCS of wind turbines in the weather radar frequency bands by means of computer simulations based on the physical optics theory and then proposes a simplified model to estimate wind turbine RCS values. This model is of great help in the evaluation of the potential impact of a certain wind farm on the weather radar operation.

  14. Disaggregating radar-derived rainfall measurements in East Azarbaijan, Iran, using a spatial random-cascade model

    NASA Astrophysics Data System (ADS)

    Fouladi Osgouei, Hojjatollah; Zarghami, Mahdi; Ashouri, Hamed

    2016-04-01

    The availability of spatial, high-resolution rainfall data is one of the most essential needs in the study of water resources. These data are extremely valuable in providing flood awareness for dense urban and industrial areas. The first part of this paper applies an optimization-based method to the calibration of radar data based on ground rainfall gauges. Then, the climatological Z-R relationship for the Sahand radar, located in the East Azarbaijan province of Iran, with the help of three adjacent rainfall stations, is obtained. The new climatological Z-R relationship with a power-law form shows acceptable statistical performance, making it suitable for radar-rainfall estimation by the Sahand radar outputs. The second part of the study develops a new heterogeneous random-cascade model for spatially disaggregating the rainfall data resulting from the power-law model. This model is applied to the radar-rainfall image data to disaggregate rainfall data with coverage area of 512 × 512 km2 to a resolution of 32 × 32 km2. Results show that the proposed model has a good ability to disaggregate rainfall data, which may lead to improvement in precipitation forecasting, and ultimately better water-resources management in this arid region, including Urmia Lake.

  15. Prediction of extreme rainfall event using weather pattern recognition and support vector machine classifier

    NASA Astrophysics Data System (ADS)

    Nayak, Munir Ahmad; Ghosh, Subimal

    2013-11-01

    A major component of flood alert broadcasting is the short-term prediction of extreme rainfall events, which remains a challenging task, even with the improvements of numerical weather prediction models. Such prediction is a high priority research challenge, specifically in highly urbanized areas like Mumbai, India, which is extremely prone to urban flooding. Here, we attempt to develop an algorithm based on a machine learning technique, support vector machine (SVM), to predict extreme rainfall with a lead time of 6-48 h in Mumbai, using mesoscale (20-200 km) and synoptic scale (200-2,000 km) weather patterns. The underlying hypothesis behind this algorithm is that the weather patterns before (6-48 h) extreme events are significantly different from those of normal weather days. The present algorithm attempts to identify those specific patterns for extreme events and applies SVM-based classifiers for extreme rainfall classification and prediction. Here, we develop the anomaly frequency method (AFM), where the predictors (and their patterns) for SVM are identified with the frequency of high anomaly values of weather variables at different pressure levels, which are present before extreme events, but absent for non-extreme conditions. We observe that weather patterns before the extreme rainfall events during nighttime (1800 to 0600Z) is different from those during daytime (0600 to 1800Z) and, accordingly, we develop a two-phase support vector classifier for extreme prediction. Though there are false alarms associated with this prediction method, the model predicts all the extreme events well in advance. The performance is compared with the state-of-the-art statistical technique fingerprinting approach and is observed to be better in terms of false alarm and prediction.

  16. Tropical Rainfall Measuring Mission (TRMM) project. VI - Spacecraft, scientific instruments, and launching rocket. Part 4 - TRMM rain radar

    NASA Technical Reports Server (NTRS)

    Meneghini, Robert; Atlas, David; Awaka, Jun; Okamoto, Ken'ichi; Ihara, Toshio; Nakamura, Kenji; Kozu, Toshiaki; Manabe, Takeshi

    1990-01-01

    The basic system parameters for the Tropical Rainfall Measuring Mission (TRMM) radar system are frequency, beamwidth, scan angle, resolution, number of independent samples, pulse repetition frequency, data rate, and so on. These parameters were chosen to satisfy NASA's mission requirements. Six candidates for the TRMM rain radar were studied. The study considered three major competitive items: (1) a pulse-compression radar vs. a conventional radar; (2) an active-array radar with a solid state power amplifier vs. a passive-array radar with a traveling-wave-tube amplifier; and (3) antenna types (planar-array antenna vs. cylindrical parabolic antenna). Basic system parameters such as radar sensitivities, power consumption, weight, and size of these six types are described. Trade-off studies of these cases show that the non-pulse-compression active-array radar with a planar array is considered to be the most suitable candidate for the TRMM rain radar at 13.8 GHz.

  17. Systematic Variation of Observed Radar Reflectivity-Rainfall Rate Relations in the Tropics.

    NASA Astrophysics Data System (ADS)

    Amitai, Eyal

    2000-12-01

    The Tropical Rainfall Measuring Mission Global Validation Program provides a unique opportunity to compare radar datasets from different sites, because they are analyzed in a relatively uniform procedure. Monthly observed radar reflectivity-rainfall rate (Ze-R) relations for four different sites that are surrounded by tipping bucket gauge networks (Melbourne, Florida; Houston, Texas; Darwin, Australia; and Kwajalein Atoll, Republic of Marshall Islands) were derived. The radar and gauge data from all sites are controlled for quality using the same algorithms, which also include an automated procedure to filter unreliable rain gauge data upon comparison with radar data. The relations are generated by two different methods. The first method is based on using a power law Ze-R with a fixed exponent of 1.4, and the second is based on matching unconditional probabilities of rain rates as measured by the gauge to radar-observed reflectivities and is known as the window probability matching method (WPMM). Both methods tune the radar observations to a network of quality-controlled gauges to adjust the total monthly rainfall to match the gauges. Separate relations are generated for convective and stratiform rain, as classified by the horizontal reflectivity structure.In the WPMM-based Ze-R relations, a given Ze was matched to a much lower R in convective rainfall than in stratiform rainfall. These relations were found to be curved lines in log-log space rather than a straight-line power law. The WPMM-based Ze-R curves demonstrated systematic variation between the convective and stratiform rain, but the power law-based Ze-R curves showed no systematic trend. The systematic variation in the relations shown here contradicts previous findings in which the classification is based only on the existence or nonexistence of brightband signature. The latter indicates a higher reflectivity in stratiform rain as compared with that in convective rain, for a given rain rate. Recent studies

  18. Using rainfall radar data to improve interpolated maps of dose rate in the Netherlands.

    PubMed

    Hiemstra, Paul H; Pebesma, Edzer J; Heuvelink, Gerard B M; Twenhöfel, Chris J W

    2010-12-01

    The radiation monitoring network in the Netherlands is designed to detect and track increased radiation levels, dose rate more specifically, in 10-minute intervals. The network consists of 153 monitoring stations. Washout of radon progeny by rainfall is the most important cause of natural variations in dose rate. The increase in dose rate at a given time is a function of the amount of progeny decaying, which in turn is a balance between deposition of progeny by rainfall and radioactive decay. The increase in progeny is closely related to average rainfall intensity over the last 2.5h. We included decay of progeny by using weighted averaged rainfall intensity, where the weight decreases back in time. The decrease in weight is related to the half-life of radon progeny. In this paper we show for a rainstorm on the 20th of July 2007 that weighted averaged rainfall intensity estimated from rainfall radar images, collected every 5min, performs much better as a predictor of increases in dose rate than using the non-averaged rainfall intensity. In addition, we show through cross-validation that including weighted averaged rainfall intensity in an interpolated map using universal kriging (UK) does not necessarily lead to a more accurate map. This might be attributed to the high density of monitoring stations in comparison to the spatial extent of a typical rain event. Reducing the network density improved the accuracy of the map when universal kriging was used instead of ordinary kriging (no trend). Consequently, in a less dense network the positive influence of including a trend is likely to increase. Furthermore, we suspect that UK better reproduces the sharp boundaries present in rainfall maps, but that the lack of short-distance monitoring station pairs prevents cross-validation from revealing this effect. PMID:20961600

  19. State-space adjustment of radar rainfall and skill score evaluation of stochastic volume forecasts in urban drainage systems.

    PubMed

    Löwe, Roland; Mikkelsen, Peter Steen; Rasmussen, Michael R; Madsen, Henrik

    2013-01-01

    Merging of radar rainfall data with rain gauge measurements is a common approach to overcome problems in deriving rain intensities from radar measurements. We extend an existing approach for adjustment of C-band radar data using state-space models and use the resulting rainfall intensities as input for forecasting outflow from two catchments in the Copenhagen area. Stochastic grey-box models are applied to create the runoff forecasts, providing us with not only a point forecast but also a quantification of the forecast uncertainty. Evaluating the results, we can show that using the adjusted radar data improves runoff forecasts compared with using the original radar data and that rain gauge measurements as forecast input are also outperformed. Combining the data merging approach with short-term rainfall forecasting algorithms may result in further improved runoff forecasts that can be used in real time control. PMID:23925186

  20. Improved accuracy of radar WPMM estimated rainfall upon application of objective classification criteria

    NASA Technical Reports Server (NTRS)

    Rosenfeld, Daniel; Amitai, Eyal; Wolff, David B.

    1995-01-01

    Application of the window probability matching method to radar and rain gauge data that have been objectively classified into different rain types resulted in distinctly different Z(sub e)-R relationships for the various classifications. These classification parameters, in addition to the range from the radar, are (a) the horizontal radial reflectivity gradients (dB/km); (b) the cloud depth, as scaled by the effective efficiency; (c) the brightband fraction within the radar field window; and (d) the height of the freezing level. Combining physical parameters to identify the type of precipitation and statistical relations most appropriate to the precipitation types results in considerable improvement of both point and areal rainfall measurements. A limiting factor in the assessment of the improved accuracy is the inherent variance between the true rain intensity at the radar measured volume and the rain intensity at the mouth of the rain guage. Therefore, a very dense rain gauge network is required to validate most of the suggested realized improvement. A rather small sample size is required to achieve a stable Z(sub e)-R relationship (standard deviation of 15% of R for a given Z(sub e)) -- about 200 mm of rainfall accumulated in all guages combined for each classification.

  1. Synoptic Analysis of Heavy Rainfall and Flood Observed in Izmir on 20 May 2015 Using Radar and Satellite Images

    NASA Astrophysics Data System (ADS)

    Avsar, Ercument

    2016-07-01

    In this study, a meteorological analysis is conducted on the sudden and heavy rainfall that occurred in Izmir on May 20, 2015. The barotropic model that is observed in upper carts is shown in detail. We can access the data of and analyze the type, severity and amount of many meteorological parameters using the meteorological radars that form a remote sensing system. The one field that uses the radars most intensively is rainfall. Images from the satellite and radar systems are used in the meteorological analysis of the heavy rainfall that occurred in Izmir on 20 May 2015, and the development of the system that led to this rainfall is shown. In this study, data received from Bornova Automatic Meteorological Observation Station (OMGI), which is under the management of Meteorology General Directorate (MGM), Izmir 2. Regional Directorate; satellite images; Radar PPI (Plan Position Indicator) and Radar MAX (Maximum Display) images are evaluated. In addition, synoptic situation, outputs of numerical estimation models, indices calculated from Skew T Log-P diagram are shown. All these results are mapped and analyzed. At the end of these analyses, it is found that this sudden rainfall had developed according to the frontal system motion. A barotropic model occurred on the day of the rainfall over the Aegean Region. As a result of the rainfall that happened in Izmir at 12.00 UTC (Universal Coordinated Time), the May month rainfall record for the last 64 years is achieved with a rainfall amount of 67.7 mm per meter square. Keywords: Izmir, barotropic model, heavy rainfall, radar, synoptic analysis

  2. Heavy rains over Chennai and surrounding areas as captured by Doppler weather radar during Northeast Monsoon 2015: a case study

    NASA Astrophysics Data System (ADS)

    Kamaljit, Ray; Kannan, B. A. M.; Stella, S.; Sen, Bikram; Sharma, Pradip; Thampi, S. B.

    2016-05-01

    During the Northeast monsoon season, India receives about 11% of its annual rainfall. Many districts in South Peninsula receive 30-60% of their annual rainfall. Coastal Tamil Nadu receives 60% of its annual rainfall and interior districts about 40-50 %. During the month of November, 2015, three synoptic scale weather systems affected Tamil Nadu and Pondicherry causing extensive rainfall activity over the region. Extremely heavy rains occurred over districts of Chennai, Thiruvallur and Kancheepuram, due to which these 3 districts were fully inundated. 122 people in Tamil Nadu were reported to have died due to the flooding, while over 70,000 people had been rescued. State government reported flood damage of the order of around Rs 8481 Crores. The rainfall received in Chennai district during 1.11.2015 to 5.12.2015 was 1416.8 mm against the normal of 408.4 mm. The extremely heavy rains were found to be associated with strong wind surges at lower tropospheric levels, which brought in lot of moisture flux over Chennai and adjoining area. The subtropical westerly trough at mid-tropospheric levels extended much southwards than its normal latitude, producing favorable environment for sustained rising motions ahead of approaching trough over coastal Tamil Nadu. Generated strong upward velocities in the clouds lifted the cloud tops to very high levels forming deep convective clouds. These clouds provided very heavy rainfall of the order of 150-200 mm/hour. In this paper we have used radar data to examine and substantiate the cloud burst that led to these torrential rains over Chennai and adjoining areas during the Northeast Monsoon period, 2015.

  3. Urban flash flood applications of high-resolution rainfall estimation by X-band dual-polarization radar network

    NASA Astrophysics Data System (ADS)

    Chandrasekar, V.; Chen, Haonan; Maki, Masayuki

    2012-11-01

    Flooding in general, especially the urban flash flooding is one of the most destructive nature hazards. Rainfall estimates from radar network are often used as input to various hydrological models for further flood warning and mitigations. The X-band dual-polarization radar network developed by the United States National Science Foundation Engineering Research Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) has shown great improvement to radar based Quantitative Precipitation Estimation (QPE), through many years of experimental validation studies. QPE and rainfall nowcasting are important goals of CASA X-band dual-polarization radar networks. This paper presents an overview of CASA QPE and nowcasting methodology. In addition, 20 rainfall events collected from the Oklahoma test best during the past 3 years are used to evaluate the networked radar rainfall products. Cross validation with a gauge network using these 20 events' data shows that the estimates of instantaneous rain rate, 5-minute,10- minute, and hourly rainfall have normalized standard error of about 47.57%, 40.03%, 34.61% and 24.78% , respectively, whereas a low bias of about -3.83%, -2.83%,-2.77% and -3.45% respectively. These evaluation results demonstrate great improvement compared to the current state-of-the-art. The paper also deals with the potential role of these highresolution rainfall products for flash floods warning and mitigation.

  4. Debris-flow forecasting at regional scale by combining susceptibility mapping and radar rainfall

    NASA Astrophysics Data System (ADS)

    Berenguer, M.; Sempere-Torres, D.; Hürlimann, M.

    2015-03-01

    This work presents a technique for debris-flow (DF) forecasting able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i) DF subbasin susceptibility assessment based on geomorphological variables and (ii) the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class warning ("low", "moderate" or "high") in each subbasin when a new radar rainfall map is available. The developed technique has been applied in a domain in the eastern Pyrenees (Spain) from May to October 2010. The warning level stayed "low" during the entire period in 20% of the subbasins, while in the most susceptible subbasins the warning level was at least "moderate" for up to 10 days. Quantitative evaluation of the warning level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the three events observed in the catchment (one debris flow and two hyperconcentrated flow events) and produced no false alarm.

  5. Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway

    NASA Astrophysics Data System (ADS)

    Blanchet, J.; Touati, J.; Lawrence, D.; Garavaglia, F.; Paquet, E.

    2015-12-01

    Simulation methods for design flood analyses require estimates of extreme precipitation for simulating maximum discharges. This article evaluates the multi-exponential weather pattern (MEWP) model, a compound model based on weather pattern classification, seasonal splitting and exponential distributions, for its suitability for use in Norway. The MEWP model is the probabilistic rainfall model used in the SCHADEX method for extreme flood estimation. Regional scores of evaluation are used in a split sample framework to compare the MEWP distribution with more general heavy-tailed distributions, in this case the Multi Generalized Pareto Weather Pattern (MGPWP) distribution. The analysis shows the clear benefit obtained from seasonal and weather pattern-based subsampling for extreme value estimation. The MEWP distribution is found to have an overall better performance as compared with the MGPWP, which tends to overfit the data and lacks robustness. Finally, we take advantage of the split sample framework to present evidence for an increase in extreme rainfall in the southwestern part of Norway during the period 1979-2009, relative to 1948-1978.

  6. Classification of rainfall events for weather forecasting purposes in andean region of Colombia

    NASA Astrophysics Data System (ADS)

    Suárez Hincapié, Joan Nathalie; Romo Melo, Liliana; Vélez Upegui, Jorge Julian; Chang, Philippe

    2016-04-01

    This work presents a comparative analysis of the results of applying different methodologies for the identification and classification of rainfall events of different duration in meteorological records of the Colombian Andean region. In this study the work area is the urban and rural area of Manizales that counts with a monitoring hydro-meteorological network. This network is composed of forty-five (45) strategically located stations, this network is composed of forty-five (45) strategically located stations where automatic weather stations record seven climate variables: air temperature, relative humidity, wind speed and direction, rainfall, solar radiation and barometric pressure. All this information is sent wirelessly every five (5) minutes to a data warehouse located at the Institute of Environmental Studies-IDEA. With obtaining the series of rainfall recorded by the hydrometeorological station Palogrande operated by the National University of Colombia in Manizales (http://froac.manizales.unal.edu.co/bodegaIdea/); it is with this information that we proceed to perform behavior analysis of other meteorological variables, monitored at surface level and that influence the occurrence of such rainfall events. To classify rainfall events different methodologies were used: The first according to Monjo (2009) where the index n of the heavy rainfall was calculated through which various types of precipitation are defined according to the intensity variability. A second methodology that permitted to produce a classification in terms of a parameter β introduced by Rice and Holmberg (1973) and adapted by Llasat and Puigcerver, (1985, 1997) and the last one where a rainfall classification is performed according to the value of its intensity following the issues raised by Linsley (1977) where the rains can be considered light, moderate and strong fall rates to 2.5 mm / h; from 2.5 to 7.6 mm / h and above this value respectively for the previous classifications. The main

  7. The impact of reflectivity correction and conversion methods to improve precipitation estimation by weather radar for an extreme low-land Mesoscale Convective System

    NASA Astrophysics Data System (ADS)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2014-05-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands. For most of the country this led to over 15 hours of near-continuous precipitation, which resulted in total event accumulations exceeding 150 mm in the eastern part of the Netherlands. Such accumulations belong to the largest sums ever recorded in this country and gave rise to local flooding. Measuring precipitation by weather radar within such mesoscale convective systems is known to be a challenge, since measurements are affected by multiple sources of error. For the current event the operational weather radar rainfall product only estimated about 30% of the actual amount of precipitation as measured by rain gauges. In the current presentation we will try to identify what gave rise to such large underestimations. In general weather radar measurement errors can be subdivided into two different groups: 1) errors affecting the volumetric reflectivity measurements taken, and 2) errors related to the conversion of reflectivity values in rainfall intensity and attenuation estimates. To correct for the first group of errors, the quality of the weather radar reflectivity data was improved by successively correcting for 1) clutter and anomalous propagation, 2) radar calibration, 3) wet radome attenuation, 4) signal attenuation and 5) the vertical profile of reflectivity. Such consistent corrections are generally not performed by operational meteorological services. Results show a large improvement in the quality of the precipitation data, however still only ~65% of the actual observed accumulations was estimated. To further improve the quality of the precipitation estimates, the second group of errors are corrected for by making use of disdrometer measurements taken in close vicinity of the radar. Based on these data the parameters of a normalized drop size distribution are estimated for the total event as well as for each precipitation type separately (convective

  8. Analysis of the influence of rainfall variables on urban effluents concentrations and fluxes in wet weather

    NASA Astrophysics Data System (ADS)

    Gooré Bi, Eustache; Monette, Frédéric; Gasperi, Johnny

    2015-04-01

    Urban rainfall runoff has been a topic of increasing importance over the past years, a result of both the increase in impervious land area arising from constant urban growth and the effects of climate change on urban drainage. The main goal of the present study is to assess and analyze the correlations between rainfall variables and common indicators of urban water quality, namely event mean concentrations (EMCs) and event fluxes (EFs), in order to identify and explain the impacts of each of the main rainfall variables on the generation process of urban pollutants during wet periods. To perform this analysis, runoff from eight summer rainfall events that resulted in combined sewer overflow (CSO) was sampled simultaneously from two distinct catchment areas in order to quantify discharges at the respective outfalls. Pearson statistical analysis of total suspended solids (TSS), chemical oxygen demand (COD), carbonaceous biochemical oxygen demand at 5 days (CBOD5), total phosphorus (Ptot) and total kedjal nitrogen (N-TKN) showed significant correlations (ρ = 0.05) between dry antecedent time (DAT) and EMCs on one hand, and between total rainfall (TR) and the volume discharged (VD) during EFs, on the other. These results show that individual rainfall variables strongly affect either EMCs or EFs and are good predictors to consider when selecting variables for statistical modeling of urban runoff quality. The results also show that in a combined sewer network, there is a linear relationship between TSS event fluxes and COD, CBOD5, Ptot, and N-TKN event fluxes; this explains 97% of the variability of these pollutants which adsorb onto TSS during wet weather, which therefore act as tracers. Consequently, the technological solution selected for TSS removal will also lead to a reduction of these pollutants. Given the huge volumes involved, urban runoffs contribute substantially to pollutant levels in receiving water bodies, a situation which, in a climate change context, may

  9. On Utilization of NEXRAD Scan Strategy Information to Infer Discrepancies Associated With Radar and Rain Gauge Surface Volumetric Rainfall Accumulations

    NASA Technical Reports Server (NTRS)

    Roy, Biswadev; Datta, Saswati; Jones, W. Linwood; Kasparis, Takis; Einaudi, Franco (Technical Monitor)

    2000-01-01

    To evaluate the Tropical Rainfall Measuring Mission (TRMM) monthly Ground Validation (GV) rain map, 42 quality controlled tipping bucket rain gauge data (1 minute interpolated rain rates) were utilized. We have compared the gauge data to the surface volumetric rainfall accumulation of NEXRAD reflectivity field, (converting to rain rates using a 0.5 dB resolution smooth Z-R table). The comparison was carried out from data collected at Melbourne, Florida during the month of July 98. GV operational level 3 (L3 monthly) accumulation algorithm was used to obtain surface volumetric accumulations for the radar. The gauge records were accumulated using the 1 minute interpolated rain rates while the radar Volume Scan (VOS) intervals remain less than or equal to 75 minutes. The correlation coefficient for the radar and gauge totals for the monthly time-scale remain at 0.93, however, a large difference was noted between the gauge and radar derived rain accumulation when the radar data interval is either 9 minute, or 10 minute. This difference in radar and gauge accumulation is being explained in terms of the radar scan strategy information. The discrepancy in terms of the Volume Coverage Pattern (VCP) of the NEXRAD is being reported where VCP mode is ascertained using the radar tilt angle information. Hourly radar and gauge accumulations have been computed using the present operational L3 method supplemented with a threshold period of +/- 5 minutes (based on a sensitivity analysis). These radar and gauge accumulations are subsequently improved using a radar hourly scan weighting factor (taking ratio of the radar scan frequency within a time bin to the 7436 total radar scans for the month). This GV procedure is further being improved by introducing a spatial smoothing method to yield reasonable bulk radar to gauge ratio for the hourly and daily scales.

  10. Network connectivity paradigm for the large data produced by weather radar systems

    NASA Astrophysics Data System (ADS)

    Guenzi, Diego; Bechini, Renzo; Boraso, Rodolfo; Cremonini, Roberto; Fratianni, Simona

    2014-05-01

    The traffic over Internet is constantly increasing; this is due in particular to social networks activities but also to the enormous exchange of data caused especially by the so-called "Internet of Things". With this term we refer to every device that has the capability of exchanging information with other devices on the web. In geoscience (and, in particular, in meteorology and climatology) there is a constantly increasing number of sensors that are used to obtain data from different sources (like weather radars, digital rain gauges, etc.). This information-gathering activity, frequently, must be followed by a complex data analysis phase, especially when we have large data sets that can be very difficult to analyze (very long historical series of large data sets, for example), like the so called big data. These activities are particularly intensive in resource consumption and they lead to new computational models (like cloud computing) and new methods for storing data (like object store, linked open data, NOSQL or NewSQL). The weather radar systems can be seen as one of the sensors mentioned above: it transmit a large amount of raw data over the network (up to 40 megabytes every five minutes), with 24h/24h continuity and in any weather condition. Weather radar are often located in peaks and in wild areas where connectivity is poor. For this reason radar measurements are sometimes processed partially on site and reduced in size to adapt them to the limited bandwidth currently available by data transmission systems. With the aim to preserve the maximum flow of information, an innovative network connectivity paradigm for the large data produced by weather radar system is here presented. The study is focused on the Monte Settepani operational weather radar system, located over a wild peak summit in north-western Italy.

  11. Estimation of Rainfall Kinetic Energy by Rain Intensity and/or Radar Reflectivity Factor

    NASA Astrophysics Data System (ADS)

    Yu, N.; Delrieu, G.; Boudevillain, B.; Hazenberg, P.; Uijlenhoet, R.

    2011-12-01

    This study presents an approach to estimate the rainfall kinetic energy (KE) by rain intensity (R) and radar reflectivity factor (Z) separately, or jointly, on the basis of a one- or two-moment scaled formulation. This formulation considers the raindrop size distribution (DSD) as a combination of bulk rainfall variable(s) (R or/and Z) and an intrinsic distribution g(x), which is in function of the scaled raindrop diameter x. Results from previous studies showed that g(x) remains more or less constant, hence the variability of DSD is mainly explained by the bulk rainfall variable(s). In this study, the Gamma probability density function (pdf) with two parameters is used to model the g(x). Considered the self-consistent relationships between parameters, a robust method is proposed to estimate three climatological g(x), in R-, Z- and RZ-scaled formulation respectively, with a 28-month DSD dataset collected in the Cevennes-Vivarais region, France. Three relationships (KE-R, KE-Z and KE-(R,Z)), which link the observations (R and/or Z) to rainfall kinetic energy (KE), are established based on three climatological g(x). As expected, the combination of R and Z yields a significant improvement of the estimation of KE compared to the single-moment formulations. And Z yields a better performance in KE estimating compared to the KE-R relationship. In terms of the application of these relationships based on real radar reflectivity factors and/or rain gauge measurements, the combination of R and Z yields also the best performance in estimation of KE among the three relationships. Different from the application of the disdrometer data, the performance of the real KE-Z relationship degrades compared to the real KE-R relationship, which is probably due to the sampling error of radar. However, KE estimated by radar possess the advantages in spatialization of kinetic energy over that based on rain gauge stations. This study was supported financially by the HYDRATE project of the

  12. Estimating reflectivity values from wind turbines for analyzing the potential impact on weather radar services

    NASA Astrophysics Data System (ADS)

    Angulo, I.; Grande, O.; Jenn, D.; Guerra, D.; de la Vega, D.

    2015-02-01

    The World Meteorological Organization (WMO) has repeatedly expressed concern over the increasing number of impact cases of wind turbine farms on weather radars. Since nowadays signal processing techniques to mitigate Wind Turbine Clutter (WTC) are scarce, the most practical approach to this issue is the assessment of the potential interference from a wind farm before it is installed. To do so, and in order to obtain a WTC reflectivity model, it is crucial to estimate the Radar Cross Section (RCS) of the wind turbines to be built, which represents the power percentage of the radar signal that is backscattered to the radar receiver. This paper first characterizes the RCS of wind turbines in the weather radar frequency bands by means of computer simulations based on the Physical Optics theory, and then proposes a simplified model to estimate wind turbine RCS values. This model is of great help in the evaluation of the potential impact of a certain wind farm on the weather radar operation.

  13. Wideband Waveform Design principles for Solid-state Weather Radars

    SciTech Connect

    Bharadwaj, Nitin; Chandrasekar, V.

    2012-01-01

    The use of solid-state transmitter is becoming a key part of the strategy to realize a network of low cost electronically steered radars. However, solid-state transmitters have low peak powers and this necessitates the use of pulse compression waveforms. In this paper a frequency diversity wideband waveforms design is proposed to mitigate low sensitivity of solid-state transmitters. In addition, the waveforms mitigate the range eclipsing problem associated with long pulse compression. An analysis of the performance of pulse compression using mismatched compression filters designed to minimize side lobe levels is presented. The impact of range side lobe level on the retrieval of Doppler moments are presented. Realistic simulations are performed based on CSU-CHILL radar data and Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project I (IP1) radar data.

  14. Operational Wind Retrieval Within the Frame of the French Weather Radar Network

    NASA Astrophysics Data System (ADS)

    Bousquet, O.; Tabary, P.; Parent-Du-Châtelet, J.; Périer, L.

    2008-12-01

    The recent deployment of an innovative triple-PRT Doppler scheme within the French operational radar network, named ARAMIS, allows collecting reflectivity and radial velocity measurements simultaneously up to a range of 250 km with no ambiguity. This achievement brings new perspectives in terms of exploitation of operational radar measurements such as the long-anticipated capability to perform multiple-Doppler wind retrieval in a fully operational framework. Accordingly, and for the first time ever, a method allowing to consistently retrieve complete wind vector fields (u, v, w) in real-time from operational radar systems is being tested by the French national weather service since early 2007. This study proposes to describe the experimental setup relied upon to operationally retrieve multiple-Doppler winds in the frame of ARAMIS, as well as to investigate the potential of this new product for weather forecast applications. Using high resolution numerical wind forecasts in a variety of weather situations, we also show that these radar-derived wind fields compose unprecedented datasets to evaluate and further improve high-resolution numerical weather prediction systems being currently deployed by many national weather services.

  15. Detection and discrimination of fauna in the aerosphere using Doppler weather surveillance radar.

    PubMed

    Gauthreaux, Sidney A; Livingston, John W; Belser, Carroll G

    2008-07-01

    Organisms in the aerosphere have been detected by radar since its development in the 1940s. The national network of Doppler weather radars (WSR-88D) in the United States can readily detect birds, bats, and insects aloft. Level-II data from the radar contain information on the reflectivity and radial velocity of targets and on width of the spectrum (SD of radial velocities in a radar pulse volume). Information on reflectivity can be used to quantify density of organisms aloft and radial velocity can be used to discriminate different types of targets based on their air speeds. Spectral width can also provide some useful information when organisms with very different air speeds are aloft. Recent work with dual-polarization radar suggests that it may be useful for discriminating birds from insects in the aerosphere, but more development and biological validation are required. PMID:21669769

  16. Evaluation of the rainfall component of a weather generator for climate impact studies

    NASA Astrophysics Data System (ADS)

    Elshamy, Mohamed Ezzat; Wheater, Howard S.; Gedney, Nicola; Huntingford, Chris

    2006-07-01

    Hydrological impacts of climate change are frequently assessed by off-line forcing of a hydrological model with climatic scenarios from either Global Circulation Models (GCMs) or simpler analogue models. Most hydrological models require a daily time step or smaller while observed climatology and GCM and analogue model output is generally available on a monthly time step. This study investigates and improves a rainfall disaggregation model currently used to convert monthly rainfall totals down to the daily time step. The performance of the model is evaluated using daily data from a network of raingauges covering the Nile basin and contrasted with data from a relatively dense raingauge network from the Blackwater Catchment, in the Southeast of the UK. Whilst the model preserves the mean properties of rainfall occurrence and depth, there is significant overestimation of rainfall variability. Regional calibration and better formulation of the generator improve simulation of variability as well as other aspects of rainfall properties. Hence the parameters required by the weather generator model cannot be regarded as universal. Proportional correction of daily amounts is applied to insure that monthly totals are preserved, allowing retention of interannual variability, and this was shown to have little effect on the distribution of wet day amounts. The calibration of parameter estimation equations has investigated spatial dependence of climate variables and parameters and found that (as expected) rainfall properties exhibit scale-dependence, which may be utilized to transfer data from one spatial scale to another. In order to complete the framework, a model is developed to estimate the wet fraction from monthly total when the former is not available.

  17. New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

    NASA Astrophysics Data System (ADS)

    Liberman, Y.; Samuels, R.; Alpert, P.; Messer, H.

    2014-10-01

    One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date, the most effective methods for large-scale rainfall estimates are radar, satellites, and, more recently, received signal level (RSL) measurements derived from commercial microwave networks (CMNs). While these methods provide improved spatial resolution over traditional rain gauges, they have their limitations as well. For example, wireless CMNs, which are comprised of microwave links (ML), are dependant upon existing infrastructure and the ML' arbitrary distribution in space. Radar, on the other hand, is known in its limitation for accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rainfall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that, by using the proposed new method, we not only generate more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show that our method outperforms CMNs or the radar alone in rain rate estimation, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, as well as the accurate rainfall measurements over large areas at sub-hourly timescales, will allow for improved understanding, initialization, and calibration of hydrological and meteorological models mainly necessary for water resource management and planning.

  18. Evaluation of a compound distribution based on weather patterns subsampling for extreme rainfall in Norway

    NASA Astrophysics Data System (ADS)

    Blanchet, J.; Touati, J.; Lawrence, D.; Garavaglia, F.; Paquet, E.

    2015-06-01

    Simulation methods for design flood analyses require estimates of extreme precipitation for simulating maximum discharges. This article evaluates the MEWP model, a compound model based on weather pattern classification, seasonal splitting and exponential distributions, for its suitability for use in Norway. The MEWP model is the probabilistic rainfall model used in the SCHADEX method for extreme flood estimation. Regional scores of evaluation are used in a split sample framework to compare the MEWP distribution with more general heavy-tailed distributions, in this case the Multi Generalized Pareto Weather Pattern (MGPWP) distribution. The analysis shows the clear benefit obtained from seasonal and weather pattern-based subsampling for extreme value estimation. The MEWP distribution is found to have an overall better performance as compared with the MGPWP, which tends to overfit the data and lacks robustness. Finally, we take advantage of the split sample framework to present evidence for an increase in extreme rainfall in the south-western part of Norway during the period 1979-2009, relative to 1948-1978.

  19. An alternative approach to estimating rainfall rate by radar using propagation differential phase shift

    NASA Technical Reports Server (NTRS)

    Jameson, A. R.

    1994-01-01

    In this work it is shown that for frequencies from 3 to 13 GHz, the ratio of the specific propagation differential phase shift phi(sub DP) to the rainfall rate can be specified essentially independently of the form of the drop size distribution by a function only of the mass-weighted mean drop size D(sub m). This significantly reduces one source of substantial bias errors common to most other techniques for measuring rain by radar. For frequencies 9 GHz and greater, the coefficient can be well estimated from the ratio of the specific differential attenuation to phi(sub DP), while at nonattenuating frequencies such as 3 GHz, the coefficient can be well estimated using the differential reflectivity. In practice it appears that this approach yields better estimates of the rainfall rate than any other current technique. The best results are most likely at 13.80 GHz, followed by those at 2.80 GHz. An optimum radar system for measuring rain should probably include components at a both frequencies so that when signals at 13.8 GHz are lost because of attenuation, good measurements are still possible at the lower frequency.

  20. Use of Passive Microwave Observations in a Radar Rainfall-Profiling Algorithm.

    NASA Astrophysics Data System (ADS)

    Grecu, Mircea; Anagnostou, Emmanouil N.

    2002-07-01

    A physically based methodology to incorporate passive microwave observations in a `rain-profiling algorithm' is developed for space- or airborne radars at frequencies exhibiting attenuation. The rain-profiling algorithm deploys a formulation for reflectivity attenuation correction that is mathematically equivalent to that of Hitschfeld and Bordan. In this formulation, the reflectivity-hydrometeor content (or rainfall rate) and reflectivity-attenuation relationships are expressed as a function of one variable in the drop size distribution parameterization, namely, the multiplicative factor in a normalized gamma distribution. The multiplicative factor parameter, mean cloud water content, and one parameter describing the precipitation phase are estimated in a Bayesian framework. This involves the minimization of differences between the 10-, 19-, 37-, and 85-GHz brightness temperature values predicted by a plane-parallel multilayer radiative transfer model and those observed by space- or airborne radiometers. A variational approach is devised to perform the minimization. The methodology is first tested using data simulated using a cloud model and is subsequently applied to coincident airborne brightness temperature and radar profile observations originating in the Kwajalein Experiment of the Tropical Rainfall Measuring Mission (TRMM). Results suggest improvements in rain estimation induced by the inclusion of the brightness temperature information in the retrieval framework if consistent modeling and quantification of errors are performed. Recommendations regarding the application of the method to TRMM satellite observations are formulated based on the findings of the study.

  1. Worldwide Weather Radar Imagery May Allow Substantial Increase in Meteorite Fall Recovery

    NASA Technical Reports Server (NTRS)

    Fries, Marc; Matson, Robert; Schaefer, Jacob; Fries, Jeffery; Hankey, Mike; Anderson, Lindsay

    2014-01-01

    Weather radar imagery is a valuable new technique for the rapid recovery of meteorite falls, to include falls which would not otherwise be recovered (e.g. Battle Mountain). Weather radar imagery reveals about one new meteorite fall per year (18 falls since 1998), using weather radars in the United States alone. However, an additional 75 other nations operate weather radar networks according to the UN World Meteorological Organization (WMO). If the imagery of those radars were analyzed, the current rate of meteorite falls could be improved considerably, to as much as 3.6 times the current recovery rate based on comparison of total radar areal coverage. Recently, the addition of weather radar imagery, seismometry and internet-based aggregation of eyewitness reports has improved the speed and accuracy of fresh meteorite fall recovery [e.g. 1,2]. This was demonstrated recently with the radar-enabled recovery of the Sutter's Mill fall [3]. Arguably, the meteorites recovered via these methods are of special scientific value as they are relatively unweathered, fresh falls. To illustrate this, a recent SAO/NASA ADS search using the keyword "meteorite" shows that all 50 of the top search results included at least one named meteorite recovered from a meteorite fall. This is true even though only 1260 named meteorite falls are recorded among the >49,000 individual falls recorded in the Meteoritical Society online database. The US NEXRAD system used thus far to locate meteorite falls covers most of the United States' surface area. Using a WMO map of the world's weather radars, we estimate that the total coverage of the other 75 national weather radar networks equals about 3.6x NEXRAD's coverage area. There are two findings to draw from this calculation: 1) For the past 16 years during which 18 falls are seen in US radar data, there should be an additional 65 meteorite falls recorded in worldwide radar imagery. Also: 2) if all of the world's radar data could be analyzed, the

  2. The value of weather radar data for the estimation of design storms - an analysis for the Hannover region

    NASA Astrophysics Data System (ADS)

    Haberlandt, Uwe; Berndt, Christian

    2016-05-01

    Pure radar rainfall, station rainfall and radar-station merging products are analysed regarding extreme rainfall frequencies with durations from 5 min to 6 h and return periods from 1 year to 30 years. Partial duration series of the extremes are derived from the data and probability distributions are fitted. The performance of the design rainfall estimates is assessed based on cross validations for observed station points, which are used as reference. For design rainfall estimation using the pure radar data, the pixel value at the station location is taken; for the merging products, spatial interpolation methods are applied. The results show, that pure radar data are not suitable for the estimation of extremes. They usually lead to an overestimation compared to the observations, which is opposite to the usual behaviour of the radar rainfall. The merging products between radar and station data on the other hand lead usually to an underestimation. They can only outperform the station observations for longer durations. The main problem for a good estimation of extremes seems to be the poor radar data quality.

  3. Use of Historical Radar Rainfall Estimates to Develop Design Storms in Los Angeles.

    NASA Astrophysics Data System (ADS)

    Curtis, D. C.; Humphrey, J.; Moffitt, J.

    2007-12-01

    A database of 15-minute historical gage adjusted radar-rainfall estimates was used to evaluate the geometric properties of storms in the City of Los Angeles, CA. The database includes selected months containing significant rainfall during the period 1996-2007. For each time step, areas of contiguous rainfall were identified as individual storm cells. An idealized ellipse was fit to each storm cell and the properties of the ellipse (e.g., size, shape, orientation, velocity and other parameters) were recorded. To accurately account for the range of storm cell sizes, capture a large number of storm cells in a climatologically similar area, assess the variability of storm movement, and minimize the impact of edge effects (i.e., incomplete coverage of cells entering and leaving), a study area substantially larger than the City of Los Angeles was used. The study area extends from city center to 30 miles north to the crest of San Gabriel Mountains, 45 miles east to Ontario, 60 miles south to Santa Catalina Island, and 70 miles west to Oxnard, an area of about10,000 square miles. Radar data for this area over 30 months in the study yields many thousands of storm cells for analysis. Storms were separated into classes by origin, direction and speed of movement. Preliminary investigations considers three types: Arctic origin (west-northwest), Pacific origin (southwest) and Tropical origin (south or stationary). Radar data (for 1996-2007) and upper air maps (1948-2006) are used to identify the direction and speed of significant precipitation events. Typical duration and temporal patterns of Los Angeles historical storms were described by season and storm type. Time of maximum intensity loading variation were determined for a selection of historic storms Depth-Areal Reduction Factors (DARF) for cloudbursts were developedfrom the radar data. These data curves are fit to equations showing the relationships between DARF, area and central intensity. Separate DARF curves are

  4. A System Concept for the Advanced Post-TRMM Rainfall Profiling Radars

    NASA Technical Reports Server (NTRS)

    Im, Eastwood; Smith, Eric A.

    1998-01-01

    Atmospheric latent heating field is fundamental to all modes of atmospheric circulation and upper mixed layer circulations of the ocean. The key to understanding the atmospheric heating process is understanding how and where precipitation occurs. The principal atmospheric processes which link precipitation to atmospheric circulation include: (1) convective mass fluxes in the form of updrafts and downdrafts; (2) microphysical. nucleation and growth of hydrometeors; and (3) latent heating through dynamical controls on the gravitation-driven vertical mass flux of precipitation. It is well-known that surface and near-surface rainfall are two of the key forcing functions on a number of geophysical parameters at the surface-air interface. Over ocean, rainfall variation contributes to the redistribution of water salinity, sea surface temperature, fresh water supply, and marine biology and eco-system. Over land, rainfall plays a significant role in rainforest ecology and chemistry, land hydrology and surface runoff. Precipitation has also been closely linked to a number of atmospheric anomalies and natural hazards that occur at various time scales, including hurricanes, cyclones, tropical depressions, flash floods, droughts, and most noticeable of all, the El Ninos. From this point of view, the significance of global atmospheric precipitation has gone far beyond the science arena - it has a far-reaching impact on human's socio-economic well-being and sustenance. These and many other science applications require the knowledge of, in a global basis, the vertical rain structures, including vertical motion, rain intensity, differentiation of the precipitating hydrometeors' phase state, and the classification of mesoscale physical structure of the rain systems. The only direct means to obtain such information is the use of a spaceborne profiling radar. It is important to mention that the Tropical Rainfall Measuring Mission (TRMM) have made a great stride forward towards this

  5. MicroRadarNet: A network of weather micro radars for the identification of local high resolution precipitation patterns

    NASA Astrophysics Data System (ADS)

    Turso, S.; Paolella, S.; Gabella, M.; Perona, G.

    2013-01-01

    In this paper, MicroRadarNet, a novel micro radar network for continuous, unattended meteorological monitoring is presented. Key aspects and constraints are introduced. Specific design strategies are highlighted, leading to the technological implementations of this wireless, low-cost, low power consumption sensor network. Raw spatial and temporal datasets are processed on-board in real-time, featuring a consistent evaluation of the signals from the sensors and optimizing the data loads to be transmitted. Network servers perform the final post-elaboration steps on the data streams coming from each unit. Final network products are meteorological mappings of weather events, monitored with high spatial and temporal resolution, and lastly served to the end user through any Web browser. This networked approach is shown to imply a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range monitoring strategy. Adoption of the TITAN storm identification and nowcasting engine is also here evaluated for in-loop integration within the MicroRadarNet data processing chain. A brief description of the engine workflow is provided, to present preliminary feasibility results and performance estimates. The outcomes were not so predictable, taking into account relevant operational differences between a Western Alps micro radar scenario and the long range radar context in the Denver region of Colorado. Finally, positive results from a set of case studies are discussed, motivating further refinements and integration activities.

  6. On Rainfall Modification by Major Urban Areas. Part 1; Observations from Space-borne Rain Radar Aboard TRMM

    NASA Technical Reports Server (NTRS)

    Shepherd, J. Marshell; Starr, David OC. (Technical Monitor)

    2001-01-01

    A novel approach is introduced to correlating urbanization and rainfall modification. This study represents one of the first published attempts (possibly the first) to identify and quantify rainfall modification by urban areas using satellite-based rainfall measurements. Previous investigations successfully used rain gauge networks and around-based radar to investigate this phenomenon but still encountered difficulties due to limited, specialized measurements and separation of topographic and other influences. Three years of mean monthly rainfall rates derived from the first space-based rainfall radar, Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of data at half-degree latitude resolution enables identification of rainfall patterns around major metropolitan areas of Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Preliminary results reveal an average increase of 5.6% in monthly rainfall rates (relative to a mean upwind CONTROL area) over the metropolis but an average increase of approx. 28%, in monthly rainfall rates within 30-60 kilometers downwind of the metropolis. Some portions of the downwind area exhibit increases as high as 51%. It was also found that maximum rainfall rates found in the downwind impact area exceeded the mean value in the upwind CONTROL area by 48%-116% and were generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are quite consistent studies of St. Louis (e.g' METROMEX) and Chicago almost two decades ago and more recent studies in the Atlanta and Mexico City areas.

  7. Comparison between weather radar and rain gauges data of precipitations that triggered debris flows in the Dolomites (North Eastern Italian Alps)

    NASA Astrophysics Data System (ADS)

    Bernard, Martino; Gregoretti, Carlo

    2016-04-01

    High intensity and short duration (usually 15-30 minutes) rainfalls are able to generate sudden and abundant runoff in rocky cliffs that can entrain large quantities of sediments and originate debris flow phenomena. A rain gauge network has been set up in two different areas of Dolomites (North Eastern Italian Alps) far each other about 15 km: Fiames (Cortina d'Ampezzo) and Rovina di Cancia (Borca di Cadore). The first network is composed of 9 rain gauges in an area of 1 km2, while the second is composed of 6 rain gauges in an area of 2 km2. In both the areas, the rain gauges are positioned both upstream and downstream the initiation areas of the occurring debris flows. Another single rain gauge is positioned close to the initiation area of Rudavoi debris flow (Auronzo di Cadore) and is far about 5 km from the Fiames rain gauges network. All the rain gauges sample precipitation depth at 5 minutes intervals. In the years 2009-2015 records of rainfalls that triggered 22 debris flows were taken. In most cases, the recorded rainfalls show an higher variability both along distance (200-500 m) and along altitude (200-600 m). Precipitation data recorded by the rain gauges are then compared with those estimated by means of a C-Band weather radar about 70 km away from there, to verify the possible interchangeability of the two measurement systems. Rainfall depths estimated by radar are provided with the temporal interval of the rain gauges (5 minutes) but with a different spatial scale (500 x 500 m raster resolution). To avoid the observation scale gap between the different techniques, in addition to standard comparisons between point gauge and radar rainfall measures, mean areal precipitations were derived from rain gauge network and compared with radar data. Results seem to demonstrate that radar tends to underestimate precipitation evaluated from rain gauges network, both on different measurement scales and on mean spatial data. On average, underestimation regards both

  8. A Gaussian field for aggregation and disaggregation of radar rainfall data

    NASA Astrophysics Data System (ADS)

    Krebsbach, Katharina; Friederichs, Petra

    2014-05-01

    The generation of reliable precipitation products that explicitly account for spatial and temporal structures of precipitation events is challenging, since it requires a combination of data with a variety of error structures and temporal resolutions. In-situ measurements are relatively accurate quantities, but available only at sparse and irregularly distributed locations. Remote measurements cover complete areas but suffer from spatially and temporally inhomogeneous systematic errors and non-linear relations between the measured value reflectivity and the precipitation rate. Our aim is to provide a statistical model based on a latent Gaussian random field that suitably models radar precipitation rates and enables us to aggregate and disaggregate them in space and time. We first transform radar rainfall rates such that they follow a truncated Gaussian distribution using a power transformation proposed by D. Allcroft and C. Glasbey (2003). The advantage of using a truncated Gaussian random field is that occurrence and intensity of rainfall are modeled using a single process. To parameterize the latent Gaussian random field we estimate the empirical correlation as function of lag distance in space using the maximum likelihood method and fit a parametric correlation function to the estimates. This yields a spatial Gaussian random field. The transformation only allocates censored values to dry locations, i.e. the locations below some threshold. In order to obtain a Gaussian random field that covers the whole domain, we need to simulate the unobserved values below the threshold conditional on the observed values. The parametrically defined Gaussian random field now allows us to aggregate and disaggregate the radar measurements to different scales and compare them to measurements from ground based instruments.

  9. Coupling Radar Rainfall Estimation and Hydrological Modelling For Flash-flood Hazard Mitigation

    NASA Astrophysics Data System (ADS)

    Borga, M.; Creutin, J. D.

    issues are examined: advantages and caveats of using radar rainfall estimates in operational flash flood forecasting, methodological problems as- sociated to the use of hydrological models for distributed flash flood forecasting with rainfall input estimated from radar.

  10. Use of radar rainfall data for high-resolution flash flood forecasting in the Dallas-Fort Worth Metroplex area

    NASA Astrophysics Data System (ADS)

    Seo, D. J.; Habibi, H.; Rafieei Nasab, A.; Norouzi, A.; Nazari, B.; Lee, H. S.; Cosgrove, B.; Cui, Z.

    2015-12-01

    For monitoring and prediction of water-related hazards such as flash flooding in urban areas, high-resolution hydrologic and hydraulic modeling is necessary. Because of large sensitivity and scale dependence of rainfall-runoff models to errors in quantitative precipitation estimates (QPE), it is important that the accuracy of QPE be improved to the greatest extent possible. In this presentation, we describe the ongoing efforts in the Dallas-Fort Worth Metroplex area to provide location- and time-specific flash flooding warnings in real-time. The hydrologic modeling system used is the National Weather Service (NWS) Hydrology Laboratory's Research Distributed Hydrologic Model (HLRDHM) applied at spatiotemporal resolutions ranging from 250 m to 2 km and from 1 min to 1 hour. The high-resolution precipitation input is from the DFW Demonstration Network of the Collaborative Adaptive Sensing of the Atmosphere (CASA) radars, the Next Generation QPE (Q2), and the NWS Multisensor Precipitation Estimator (MPE). Also described are the assessment of sensitivity of streamflow simulation to the spatiotemporal resolution of precipitation input and hydrologic modeling, the needs for high-quality high-resolution precipitation data sets for hydro-meteorological and -climatological applications particularly in large urban areas, and possible approaches to realize them.

  11. Comparison of Radar Rainfall Retrieval Algorithms in Convective Rain During TOGA COARE

    NASA Technical Reports Server (NTRS)

    Durden, Stephen L.; Haddad, Z. S.

    1998-01-01

    The authors compare deterministic and stochastic rain-rate retrieval algorithms by applying them to 14-GHz nadir-looking airborne radar reflectivity profiles acquired in tropical convective rain during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment, The deterministic algorithms both use the path-integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the k-R relation, while the second corrects the Z-R relation. The stochastic algorithms are based on applying an extended Kalman filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. The authors find that the stochastic algorithm, which uses the PIA, is the most robust algorithm with regard to incorrect assumptions about the drop size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA, The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions.

  12. A distributed model for slope stability analysis using radar detected rainfall intensity

    NASA Astrophysics Data System (ADS)

    Leoni, L.; Rossi, G.; Catani, F.

    2009-04-01

    The term shallow landslides is widely used in literature to describe a slope movement of limited size that mainly develops in soils up to a maximum of a few meters. Shallow landslides are usually triggered by heavy rainfall because, as the water starts to infiltrate in the soil, the pore-water pressure increases so that the shear strength of the soil is reduced leading to slope failure. We have developed a distributed hydrological-geotechnical model for the forecasting of the temporal and spatial distribution of shallow landslides to be used as a warning system for civil protection purpose. The model uses radar detected rainfall intensity as the input for the hydrological simulation of the infiltration. Using the rainfall pattern detected by the radar is in fact possible to dynamically control the redistribution of groundwater pressure associated with transient infiltration of rain so as to infer the slope stability of the studied area. The model deals with both saturated and unsaturated conditions taking into account the effect of soil suction when the soil is not completely saturated. Two pilot sites have been chosen to develop and test this model: the Armea basin (Liguria, Italy) and the Ischia Island (Campania, Italy). In recent years several severe rainstorms have occurred in both these areas. In at least two cases these have triggered numerous shallow landslides that have caused victims and damaged roads, buildings and agricultural activities. In its current stage, the basic basin-scale model applied for predicting the probable location of shallow landslides involves several stand-alone components. The solution suggested by Iverson for the Richards equation is used to estimate the transient groundwater pressure head distribution according to radar detected rainfall intensity. A soil depth prediction scheme and a limit-equilibrium infinite slope stability algorithm are used to calculate the distributed factor of safety (FS) at different depths and to record

  13. New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

    NASA Astrophysics Data System (ADS)

    Liberman, Y.; Samuels, R.; Alpert, P.; Messer, H.

    2014-05-01

    One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date the most effective methods for large scale rainfall estimates are radar, satellites, and more recently, received signal level (RSL) measurements received from commercial microwave networks (CMN). While these methods provide improved spatial resolution over traditional rain gauges, these have their limitations as well. For example, the wireless CMN, which are comprised of microwave links (ML), are dependant upon existing infrastructure, and the ML arbitrary distribution in space. Radar, on the other hand, is known in its limitation in accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rain fall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that by using the proposed new method we not only generate a more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show an improvement of rain rate estimation over CMN or radar alone, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, and the accurate rainfall measurements over large areas at sub-hourly time scales, will allow for improved understanding, initialization and calibration of hydrological and meteorological models necessary, mainly, for water resource management and planning.

  14. Terminal Doppler Weather Radar (TDWR) system characteristics and design constraints

    NASA Astrophysics Data System (ADS)

    Wieler, J. G.; Shrader, W. W.

    TDWR features two scan strategies: hazardous weather mode and monitor mode; the system has redundant transmitters, receiver/exciters, and signal processing channels. The data processing system features data base formation/conditioning, clutter residue editing, point target removal, signal-to-noise thresholding, velocity dealiasing, and a pulse-repetition frequency selection/deobscuration algorithm.

  15. Navigation errors encountered using weather-mapping radar for helicopter IFR guidance to oil rigs

    NASA Technical Reports Server (NTRS)

    Phillips, J. D.; Bull, J. S.; Hegarty, D. M.; Dugan, D. C.

    1980-01-01

    In 1978 a joint NASA-FAA helicopter flight test was conducted to examine the use of weather-mapping radar for IFR guidance during landing approaches to oil rig helipads. The following navigation errors were measured: total system error, radar-range error, radar-bearing error, and flight technical error. Three problem areas were identified: (1) operational problems leading to pilot blunders, (2) poor navigation to the downwind final approach point, and (3) pure homing on final approach. Analysis of these problem areas suggests improvement in the radar equipment, approach procedure, and pilot training, and gives valuable insight into the development of future navigation aids to serve the off-shore oil industry.

  16. The Federal Aviation Administration/Massachusetts Institute of Technology (FAA/MIT) Lincoln Laboratory Doppler weather radar program

    NASA Technical Reports Server (NTRS)

    Evans, James E.

    1988-01-01

    The program focuses on providing real-time information on hazardous aviation weather to end users such as air traffic control and pilots. Existing systems will soon be replaced by a Next Generation Weather Radar (NEXRAD), which will be concerned with detecting such hazards as heavy rain and hail, turbulence, low-altitude wind shear, and mesocyclones and tornadoes. Other systems in process are the Central Weather Processor (CWP), and the terminal Doppler weather radar (TDWR). Weather measurements near Memphis are central to ongoing work, especially in the area of microbursts and wind shear.

  17. 5 year radar-based rainfall statistics: disturbances analysis and development of a post-correction scheme for the German radar composite

    NASA Astrophysics Data System (ADS)

    Wagner, A.; Seltmann, J.; Kunstmann, H.

    2015-02-01

    A radar-based rainfall statistic demands high quality data that provide realistic precipitation amounts in space and time. Instead of correcting single radar images, we developed a post-correction scheme for long-term composite radar data that corrects corrupted areas, but preserves the original precipitation patterns. The post-correction scheme is based on a 5 year statistical analysis of radar composite data and its constituents. The accumulation of radar images reveals artificial effects that are not visible in the individual radar images. Some of them are already inherent to single radar data such as the effect of increasing beam height, beam blockage or clutter remnants. More artificial effects are introduced in the process of compositing such as sharp gradients at the boundaries of overlapping areas due to different beam heights and resolution. The cause of these disturbances, their behaviour with respect to reflectivity level, season or altitude is analysed based on time-series of two radar products: the single radar reflectivity product PX for each of the 16 radar systems of the German Meteorological Service (DWD) for the time span 2000 to 2006 and the radar composite product RX of DWD from 2005 through to 2009. These statistics result in additional quality information on radar data that is not available elsewhere. The resulting robust characteristics of disturbances, e.g. the dependency of the frequencies of occurrence of radar reflectivities on beam height, are then used as a basis for the post-correction algorithm. The scheme comprises corrections for shading effects and speckles, such as clutter remnants or overfiltering, as well as for systematic differences in frequencies of occurrence of radar reflectivities between the near and the far ranges of individual radar sites. An adjustment to rain gauges is also included. Applying this correction, the Root-Mean-Square-Error for the comparison of radar derived annual rain amounts with rain gauge data

  18. Effect of simulated rainfall and weathering on release of preservative elements from CCA treated wood.

    PubMed

    Lebow, Stan; Williams, R Sam; Lebow, Patricia

    2003-09-15

    The release of arsenic from wood pressure-treated with chromated copper arsenate (CCA) can be decreased by application of wood finishes, but little is known about the types of finishes that are best suited for this purpose. This study evaluated the effects of finish water repellent content and ultraviolet (UV) radiation on the release of arsenic, copper, and chromium from CCA-treated wood exposed to simulated rainfall. Deck boards treated with CCA were either left unfinished or dipped in a finish prepared with 1%, 3%, or 5% water repellent. All specimens were exposed to leaching from simulated rainfall, and a subset of specimens was also exposed to UV radiation. The rainfall was collected and analyzed for total elemental arsenic, copper, and chromium. The water repellent significantly decreased the amounts of these elements in the runoff, but for the short duration of this study there was no difference among the three water repellent concentrations. It is possible that water repellent content would have a greater effect over a longer exposure period. Exposure to UV radiation caused a significant increase in leaching from both finished and unfinished specimens. This effect may be a result of increased surface area during weathering as well as loss of fibers caused by UV-induced surface erosion. PMID:14524438

  19. On Rainfall Modification by Major Urban Areas. Part 1; Observations from Space-borne Rain Radar on TRMM

    NASA Technical Reports Server (NTRS)

    Shepherd, J. Marshall; Pierce, Harold; Starr, David OC. (Technical Monitor)

    2001-01-01

    This study represents one of the first published attempts to identify rainfall modification by urban areas using satellite-based rainfall measurements. Data from the first space-based rain-radar, the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar, are employed. Analysis of the data enables identification of rainfall patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas during the warm season. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage chances are relative to an upwind CONTROL area. It was also found that maximum rainfall rates in the downwind impact area can exceed the mean value in the upwind CONTROL area by 48%-116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. These results are consistent with METROMEX studies of St. Louis almost two decades ago and more recent studies near Atlanta. Future work will investi(yate hypothesized factors causing rainfall modification by urban areas. Additional work is also needed to provide more robust validation of space-based rain estimates near major urban areas. Such research has implications for urban planning, water resource management, and understanding human impact on the environment.

  20. Better Weather Prediction and Climate Diagnostics Using Rainfall Measurements from Space

    NASA Technical Reports Server (NTRS)

    Hou, Arthur; Zhang, Sara; Li, Jui-Lin; Reale, Oreste

    2002-01-01

    Progress in understanding of the role of water in global weather and climate is currently limited by our knowledge of the spatial and temporal variability of primary hydrological fields such as precipitation and evaporation. The Tropical Rainfall Measuring Mission (TRMM) has recently demonstrated that use of microwave-based rainfall observations from space in data assimilation can provide better climate data sets and improve short-range weather forecasting. At NASA, we have been exploring non-traditional approaches to assimilating TRMM Microwave Imager (TMI) and Special Sensor Microwavehager (SSM/I) surface rain rate and latent heating profile information in global systems. In this talk we show that assimilating microwave rain rates using a continuous variational assimilation scheme based on moisture tendency corrections improves quantitative precipitation estimates (QPE) and related clouds, radiation energy fluxes, and large-scale circulations in the Goddard Earth Observing System (GEOS) reanalyses. Short-range forecasts initialized with these improved analyses also yield better QPE scores and storm track predictions for Hurricanes Bonnie and Floyd. We present a status report on current efforts to assimilate convective and stratiform latent heating profile information within the general variational framework of model parameter estimation to seek further improvements. Within the next 5 years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007/2008. Based on what has been learned from TRMM, there is a high degree of confidence that these observations can play a'major role in improving weather forecasts and producing better global datasets for understanding the Earth's water and energy cycle. The key to success is to adopt an

  1. COSMO-SkyMed measurements in precipitation over the sea: analysis of Louisiana summer thunderstorms by simultaneous weather radar observations

    NASA Astrophysics Data System (ADS)

    Roberto, N.; Baldini, L.; Gorgucci, E.; Facheris, L.; Chandrasekar, V.

    2012-04-01

    Radar signatures of rain cells are investigated using X-band synthetic aperture radar (X-SAR) images acquired from COSMO-SkyMed constellation over oceans off the coast of Louisiana in summer 2010 provided by ASI archive. COSMO-SkyMed (CSK) monitoring of Deepwater Horizon oil spill provided a big amount of data during the period April-September 2010 and in July-August when several thunderstorms occurred in that area. In X-SAR images, radar signatures of rain cells over the sea usually consist of irregularly shaped bright and dark patches. These signatures originate from 1) the scattering and attenuation of radiation by hydrometers in the rain cells and 2) the modification of the sea roughness induced by the impact of raindrops and by wind gusts associated with rain cell. However, the interpretation of precipitation signatures in X-SAR images is not completely straightforward, especially over sea. Coincident measurements from ground based radars and an electromagnetic (EM) model predicting radar returns from the sea surface corrugated by rainfall are used to support the analysis. A dataset consisting of 4 CSK images has been collected over Gulf of Mexico while a WSR-88D NEXRAD S-band Doppler radar (KLIX) located in New Orleans was scanning the nearby portion of ocean. Terrestrial measurements have been used to reconstruct the component of X-SAR returns due to precipitation by modifying the known technique applied on measurements over land (Fritz et al. 2010, Baldini et al. 2011). Results confirm that the attenuation signature in X-SAR images collected over land, particularly pronounced in the presence of heavy precipitation cells, can be related to the S-band radar reflectivity integrated along the same path. The Normalized Radar Cross Section (NRCS) of land is considered to vary usually up to a few dBs in case of rain but with strong dependency on the specific type and conditions of land cover. While the NRCS of sea surface in clear weather condition can be

  2. National Scale Rainfall Map Based on Linearly Interpolated Data from Automated Weather Stations and Rain Gauges

    NASA Astrophysics Data System (ADS)

    Alconis, Jenalyn; Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo; Lester Saddi, Ivan; Mongaya, Candeze; Figueroa, Kathleen Gay

    2014-05-01

    In response to the slew of disasters that devastates the Philippines on a regular basis, the national government put in place a program to address this problem. The Nationwide Operational Assessment of Hazards, or Project NOAH, consolidates the diverse scientific research being done and pushes the knowledge gained to the forefront of disaster risk reduction and management. Current activities of the project include installing rain gauges and water level sensors, conducting LIDAR surveys of critical river basins, geo-hazard mapping, and running information education campaigns. Approximately 700 automated weather stations and rain gauges installed in strategic locations in the Philippines hold the groundwork for the rainfall visualization system in the Project NOAH web portal at http://noah.dost.gov.ph. The system uses near real-time data from these stations installed in critical river basins. The sensors record the amount of rainfall in a particular area as point data updated every 10 to 15 minutes. The sensor sends the data to a central server either via GSM network or satellite data transfer for redundancy. The web portal displays the sensors as a placemarks layer on a map. When a placemark is clicked, it displays a graph of the rainfall data for the past 24 hours. The rainfall data is harvested by batch determined by a one-hour time frame. The program uses linear interpolation as the methodology implemented to visually represent a near real-time rainfall map. The algorithm allows very fast processing which is essential in near real-time systems. As more sensors are installed, precision is improved. This visualized dataset enables users to quickly discern where heavy rainfall is concentrated. It has proven invaluable on numerous occasions, such as last August 2013 when intense to torrential rains brought about by the enhanced Southwest Monsoon caused massive flooding in Metro Manila. Coupled with observations from Doppler imagery and water level sensors along the

  3. Least square spline decomposition in time-frequency analysis of weather radar signals

    NASA Astrophysics Data System (ADS)

    Shelevytska, K. I.; Semenova, O. S.; Shelevytsky, I. V.; Yanovsky, F. J.

    2011-10-01

    Meteorology plays an important role in aviation, as it enables to predict weather conditions and detect flight dangerous meteorological phenomena. Meteorological radar is used to detect the intensity and possible location of precipitation and dangerous zones in them. Doppler radar systems are able to measure the speed of scatteres that constitute meteorological formations and phenomena. The tasks of measurement accuracy increasing and reliability rise of hazardous meteorological phenomena detection become much more relevant after establishing new flight control system CNS ATM adopted by ICAO - the International Civil Aviation Organization.

  4. Predicting combined sewer overflows chamber depth using artificial neural networks with rainfall radar data.

    PubMed

    Mounce, S R; Shepherd, W; Sailor, G; Shucksmith, J; Saul, A J

    2014-01-01

    Combined sewer overflows (CSOs) represent a common feature in combined urban drainage systems and are used to discharge excess water to the environment during heavy storms. To better understand the performance of CSOs, the UK water industry has installed a large number of monitoring systems that provide data for these assets. This paper presents research into the prediction of the hydraulic performance of CSOs using artificial neural networks (ANN) as an alternative to hydraulic models. Previous work has explored using an ANN model for the prediction of chamber depth using time series for depth and rain gauge data. Rainfall intensity data that can be provided by rainfall radar devices can be used to improve on this approach. Results are presented using real data from a CSO for a catchment in the North of England, UK. An ANN model trained with the pseudo-inverse rule was shown to be capable of predicting CSO depth with less than 5% error for predictions more than 1 hour ahead for unseen data. Such predictive approaches are important to the future management of combined sewer systems. PMID:24647201

  5. Time-lapse borehole radar for monitoring rainfall infiltration through podosol horizons in a sandy vadose zone

    NASA Astrophysics Data System (ADS)

    Strobach, Elmar; Harris, B. D.; Dupuis, J. C.; Kepic, A. W.

    2014-03-01

    The shallow aquifer on the Gnangara Mound, north of Perth, Western Australia, is recharged by winter rainfall. Water infiltrates through a sandy Podosol where cemented accumulation (B-) horizons are common. They are water retentive and may impede recharge. To observe wetting fronts and the influence of soil horizons on unsaturated flow, we deployed time-lapse borehole radar techniques sensitive to soil moisture variations during an annual recharge cycle. Zero-offset crosswell profiling (ZOP) and vertical radar profiling (VRP) measurements were performed at six sites on a monthly basis before, during, and after annual rainfall in 2011. Water content profiles are derived from ZOP logs acquired in closely spaced wells. Sites with small separation between wells present potential repeatability and accuracy difficulties. Such problems could be lessened by (i) ZOP saturated zone velocity matching of time-lapse curves, and (ii) matching of ZOP and VRP results. The moisture contents for the baseline condition and subsequent observations are computed using the Topp relationship. Time-lapse moisture curves reveal characteristic vadose zone infiltration regimes. Examples are (I) full recharge potential after 200 mm rainfall, (II) delayed wetting and impeded recharge, and (III) no recharge below 7 m depth. Seasonal infiltration trends derived from long-term time-lapse neutron logging at several sites are shown to be comparable with infiltration trends recovered from time-lapse crosswell radar measurements. However, radar measurements sample a larger volume of earth while being safer to deploy than the neutron method which employs a radioactive source. For the regime (III) site, where time-lapse radar indicates no net recharge or zero flux to the water table, a simple water balance provides an evapotranspiration value of 620 mm for the study period. This value compares favorably to previous studies at similar test sites in the region. Our six field examples demonstrate

  6. Identification of Aviation Weather Hazards Based on the Integration of Radar and Lightning Data.

    NASA Astrophysics Data System (ADS)

    Stern, Andrew D.; Brady, Raymond H., III; Moore, Patrick D.; Carter, Gary M.

    1994-12-01

    The National Weather Service Eastern Region is carrying out a national risk-reduction exercise at the Baltimore-Washington Forecast Office in Sterling, Virginia. The primary objective of this project is to integrate information from remote sensor technologies to produce comprehensive state-of-the-atmosphere reports that promote aviation safety. Techniques have been developed and tested to identify aviation-oriented hazardous weather based on data from conventional radars, a national lightning detection network, and collateral observations from new Automated Surface Observing System (ASOS) sites that are being deployed throughout the nation. From July through September 1993, an experimental observational product to identify convective activity within 30 n mi of six airports from southern Virginia to Delaware was transmitted three times each hour to personnel at Weather Service Offices and Center Weather Service Units and to the meteorologists and flight dispatchers of five major air carriers. This user-oriented evaluation and the associated statistical analysis has provided important feedback to assess the utility of the product as a supplement to ASOS. Integration of information from several products generated by the new Doppler radar at Sterling with lightning network data is being pursued for the second phase of the project. The National Weather Service will determine the viability of this approach to generate products to routinely supplement the information provided by ASOS on either a national or a local basis.

  7. Development and flight test of a weather radar precision approach concept

    NASA Technical Reports Server (NTRS)

    Clary, G. R.; Anderson, D. J.; Chisholm, J. P.

    1984-01-01

    In order to make full use of the helicopter's unique capability of remote-site, off-airport landings, it would be desirable to employ a self-contained navigation system requiring minimum groundable-based equipment. For this reason, research is being conducted with the aim to develop the use of airborne weather radar as a primary navigation aid for helicopter approach and landing in instrument flight rules (IFR) conditions. Anderson et al. (1982) have reported about the first phase of this effort, taking into account the detection of passive ground-based corner reflectors with the aid of an 'echo processor'. The technology of passive-reflector detection in the overland environment provides the pilot with the range and bearing to the landing site. The present investigation is concerned with a second research phase, which was undertaken with the objective to develop and demonstrate the feasibility of a weather radar-based precision approach concept. Preliminary flight test results are considered.

  8. Fuzzy detection and classification of dangerous weather phenomena using dual-polarimetric radar measurements

    NASA Astrophysics Data System (ADS)

    Tho Dang, Van; Yanovsky, F. J.

    2009-06-01

    A fuzzy detector and classifier of dangerous weather phenomena based on polarimetric radar measurements are described in this paper. Five polarimetric radar measurands, namely, horizontal reflectivity factor, differential reflectivity factor, linear depolarization ratio, specific differential phase, cross-correlation coefficient and altitude of resolution volume serve as inputs of the fuzzy detector and classifier. The output of the fuzzy detector and classifier is one of 8 possible classes: 0) No dangerous weather phenomenon is detected; 1) Lightning; 2) Aircraft icing; 3) Hail; 4) Hail+rain; 5) Heavy rain; 6) Wet snow; 7) Dense snow. A neural network backpropagation algorithm is also considered for training the fuzzy detector and classifier in case of having verified data.

  9. A High-Resolution 3D Weather Radar, MSG, and Lightning Sensor Observation Composite

    NASA Astrophysics Data System (ADS)

    Diederich, Malte; Senf, Fabian; Wapler, Kathrin; Simmer, Clemens

    2013-04-01

    Within the research group 'Object-based Analysis and SEamless prediction' (OASE) of the Hans Ertel Centre for Weather Research programme (HerZ), a data composite containing weather radar, lightning sensor, and Meteosat Second Generation observations is being developed for the use in object-based weather analysis and nowcasting. At present, a 3D merging scheme combines measurements of the Bonn and Jülich dual polarimetric weather radar systems (data provided by the TR32 and TERENO projects) into a 3-dimensional polar-stereographic volume grid, with 500 meters horizontal, and 250 meters vertical resolution. The merging takes into account and compensates for various observational error sources, such as attenuation through hydrometeors, beam blockage through topography and buildings, minimum detectable signal as a function of noise threshold, non-hydrometeor echos like insects, and interference from other radar systems. In addition to this, the effect of convection during the radar 5-minute volume scan pattern is mitigated through calculation of advection vectors from subsequent scans and their use for advection correction when projecting the measurements into space for any desired timestamp. The Meteosat Second Generation rapid scan service provides a scan in 12 spectral visual and infrared wavelengths every 5 minutes over Germany and Europe. These scans, together with the derived microphysical cloud parameters, are projected into the same polar stereographic grid used for the radar data. Lightning counts from the LINET lightning sensor network are also provided for every 2D grid pixel. The combined 3D radar and 2D MSG/LINET data is stored in a fully documented netCDF file for every 5 minute interval, and is made ready for tracking and object based weather analysis. At the moment, the 3D data only covers the Bonn and Jülich area, but the algorithms are planed to be adapted to the newly conceived DWD polarimetric C-Band 5 minute interval volume scan strategy. An

  10. Sub-Seasonal Variability of Tropical Rainfall Observed by TRMM and Ground-based Polarimetric Radar

    NASA Astrophysics Data System (ADS)

    Dolan, Brenda; Rutledge, Steven; Lang, Timothy; Cifelli, Robert; Nesbitt, Stephen

    2010-05-01

    Studies of tropical precipitation characteristics from the TRMM-LBA and NAME field campaigns using ground-based polarimetric S-band data have revealed significant differences in microphysical processes occurring in the various meteorological regimes sampled in those projects. In TRMM-LMA (January-February 1999 in Brazil; a TRMM ground validation experiment), variability is driven by prevailing low-level winds. During periods of low-level easterlies, deeper and more intense convection is observed, while during periods of low-level westerlies, weaker convection embedded in widespread stratiform precipitation is common. In the NAME region (North American Monsoon Experiment, summer 2004 along the west coast of Mexico), strong terrain variability drives differences in precipitation, with larger drops and larger ice mass aloft associated with convection occurring over the coastal plain compared to convection over the higher terrain of the Sierra Madre Occidental, or adjacent coastal waters. Comparisons with the TRMM precipitation radar (PR) indicate that such sub-seasonal variability in these two regions are not well characterized by the TRMM PR reflectivity and rainfall statistics. TRMM PR reflectivity profiles in the LBA region are somewhat lower than S-Pol values, particularly in the more intense easterly regime convection. In NAME, mean reflectivities are even more divergent, with TRMM profiles below those of S-Pol. In both regions, the TRMM PR does not capture rain rates above 80 mm hr-1 despite much higher rain rates estimated from the S-Pol polarimetric data, and rain rates are generally lower for a given reflectivity from TRMM PR compared to S-Pol. These differences between TRMM PR and S-Pol may arise from the inability of Z-R relationships to capture the full variability of microphysical conditions or may highlight problems with TRMM retrievals over land. In addition to the TRMM-LBA and NAME regions, analysis of sub-seasonal precipitation variability and