Science.gov

Sample records for weather radar rainfall

  1. Decision making for urban drainage systems under uncertainty caused by weather radar rainfall measurement

    NASA Astrophysics Data System (ADS)

    Dai, Qiang; Zhuo, Lu; Han, Dawei

    2015-04-01

    With the rapidly growth of urbanization and population, the decision making for managing urban flood risk has been a significant issue for most large cities in China. A high-quality measurement of rainfall at small temporal but large spatial scales is of great importance to urban flood risk management. Weather radar rainfall, with its advantage of short-term predictability and high spatial and temporal resolutions, has been widely applied in the urban drainage system modeling. It is recognized that weather radar is subjected to many uncertainties and many studies have been carried out to quantify these uncertainties in order to improve the quality of the rainfall and the corresponding outlet flow. However, considering the final action in urban flood risk management is the decision making such as flood warning and whether to build or how to operate a hydraulics structure, some uncertainties of weather radar may have little or significant influence to the final results. For this reason, in this study, we aim to investigate which characteristics of the radar rainfall are the significant ones for decision making in urban flood risk management. A radar probabilistic quantitative rainfall estimated scheme is integrated with an urban flood model (Storm Water Management Model, SWMM) to make a decision on whether to warn or not according to the decision criterions. A number of scenarios with different storm types, synoptic regime and spatial and temporal correlation are designed to analyze the relationship between these affected factors and the final decision. Based on this, parameterized radar probabilistic rainfall estimation model is established which reflects the most important elements in the decision making for urban flood risk management.

  2. 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.

  3. 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 and a parametric Bayesian approach to develop stochastic scenarios of spatial extreme rainfall fields for regional risk assessment.

  4. 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.

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. Improved estimation of heavy rainfall by weather radar after reflectivity correction and accounting for raindrop size distribution variability

    NASA Astrophysics Data System (ADS)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z-R) and radar reflectivity-specific attenuation (Z-k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

  10. 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 stratiform events, up to 80% of the values obtained with the classical non-adaptive Z-R relations.

  11. 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

  12. 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

  13. 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.

  14. Benefits and limitations of using the weather radar for the definition of rainfall thresholds for debris flows. Case study from Catalonia (Spain).

    NASA Astrophysics Data System (ADS)

    Abancó, C.; Hürlimann, M.; Sempere, D.; Berenguer, M.

    2012-04-01

    Torrential processes such as debris flows or hyperconcentrated flows are fast movements formed by a mix of water and different amounts of unsorted solid material. They occur in steep torrents and suppose a high risk for the human settlements. Rainfall is the most common triggering factor for debris flows. The rainfall threshold defines the rainfall conditions that, when reached or exceeded, are likely to provoke one or more events. Many different types of empirical rainfall thresholds for landslide triggering have been defined. Direct measurements of rainfall data are normally not available from a point next to or in the surroundings of the initiation area of the landslide. For this reason, most of the thresholds published for debris flows have been established by data measured at the nearest rain gauges (often located several km far from the landslide). Only in very few cases, the rainfall data to analyse the triggering conditions of the debris flows have been obtained by weather (Doppler) radar. Radar devices present certain limitations in mountainous regions due to undesired reboots, but their main advantage is that radar data can be obtained for any point of the territory. The objective of this work was to test the use of the weather radar data for the definition of rainfall thresholds for debris-flow triggering. Thus, rainfall data obtained from 3 to 5 rain gauges and from radar were compared for a dataset of events occurred in Catalonia (Spain). The goal was to determine in which cases the description of the rainfall episode (in particular the maximum intensity) had been more accurate. The analysed dataset consists of: 1) three events occurred in the Rebaixader debris-flow monitoring station (Axial Pyrenees) including two hyperconcentrated flows and one debris flow; 2) one debris-flow event occurred in the Port Ainé ski resort (Axial Pyrenees); 3) one debris-flow event in Montserrat (Mediterranean Coastal range). The comparison of the hyetographs from the different devices showed that the reliability of the radar is higher for short, high intensity storms more than for long lasting, medium intensity ones. Additionally, the best fit corresponds to the situations where the storm nucleus is located near the source area of the debris flow. The results of the comparison between different rain gauges show similar trends. The ones located in the same valley as the debris flow usually show good results, but if there are orographic elements in-between the debris-flow torrent and the rain gauge or the distance is large, the results can imply a great error in the definition of rainfall intensity. Therefore, we can state that the reliability of the use of the weather radar to define rainfall thresholds is strongly depending on the type of the storm and the distance between the source area and the nucleus of the storm.

  15. 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.

  16. 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 studied watersheds may sometimes remain very similar with a homogeneous rainfall input, whereas for some cases the differences in the peak discharges can reach up to 80%. A detailed analysis illustrates the possible role of the watershed in enhancing the effect of rainfall spatial variability. In a further step, the objective is to test the ability of four rainfall variability indicators to identify the situations for which spatial rainfall variability has the greatest influence on the watershed response. The selected indicators include those of Zoccatelli et al. (2010), and all rely on a detailed analysis of spatial rainfall organization in function of hydrological distances (i.e. the distances measured along the stream network from one point of the watershed to the outlet). The analysis of the links between these indicators and the hydrological behaviors identified is currently in progress. Reference: Naulin, J.P., Payrastre, O., Gaume, E., 2013. Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France. Journal of Hydrology, 486, 88-99, doi:10.1016/j.jhydrol.2013.01.044 Zoccatelli, D., Borga, M., Zanon, F., Antonescu, B., Stancalie, G., 2010. Which rainfall spatial information for flash flood response modelling? A numerical investigation based on data from the Carpathian range, Romania. Journal of Hydrology, 394, 148-161

  17. 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.

  18. 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.

  19. 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.

  20. 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 gauges location, and then interpolated back onto the radar domain, in order to obtain probabilistic radar rainfall fields in real time. The deterministic nowcasting model integrated in the STEPS system [7-8] has been used for the purpose of propagating the uncertainty and assessing the benefit of implementing the radar ensemble generator for probabilistic rainfall forecasts and ultimately sewer flow predictions. For this purpose, events representative of different types of precipitation (i.e. stratiform/convective) and significant at the urban catchment scale (i.e. in terms of sewer overflow within the urban drainage system) have been selected. As high spatial/temporal resolution is required to the forecasts for their use in urban areas [9-11], the probabilistic nowcasts have been set up to be produced at 1 km resolution and 5 min intervals. The forecasting chain is completed by a hydrodynamic model of the urban drainage network. The aim of this work is to discuss the implementation of this probabilistic system, which takes into account the radar error to characterize the forecast uncertainty, with consequent potential benefits in the management of urban systems. It will also allow a comparison with previous findings related to the analysis of different approaches to uncertainty estimation and quantification in terms of rainfall [12] and flows at the urban scale [13]. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and Dr. Alan Seed from the Australian Bureau of Meteorology for providing the radar data and the nowcasting model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1.

  1. 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 ...

  2. Rainfall small scale variability: Certain implications for radar rainfall validation problem

    NASA Astrophysics Data System (ADS)

    Habib, Emad Hosny

    Despite recent technological advances in the area of radar hydrology, reliable quantification of radar-rainfall amounts on scales relevant to hydrological applications is not fully realized. A major problem is the lack of accurate estimation of uncertainty levels of radar-rainfall products. Discrepancies between radar and rain gauge rainfall quantities---traditionally considered as an approximation of the true ground rainfall---are mainly attributed to two main factors: rainfall small-scale natural variability and differences in sampling properties between radar and gauge. The present research addresses these issues in an attempt to develop sound validation methodologies for radar-rainfall products. In the framework of this study, some fundamental questions are posed: How is rainfall variable over scales smaller than the radar-resolved scales? What role does such variability play in the evaluation of radar-rainfall estimates? Is there a radarspace/gauge-time equivalence where the observations of both sensors are possibly comparable? This study makes use of extensive experimental rainfall multi-sensor observations collected during the field campaigns of the NASA's Tropical Rainfall Measuring Mission (TRMM) in addition to other experimental datasets. First, errors associated with gauge measurements---as the main independent data source for validation---are investigated and characterized. Then, extensive data analysis is performed to characterize rainfall variability over scales relevant to radar spatial/temporal resolutions. A statistical procedure is applied to quantify the contribution of rainfall natural variability to the significant discrepancy usually observed in radar-gauge comparisons. This eventually can be used in establishing an error budget for radar-rainfall products. Finally, a non-parametric statistical procedure is developed and applied in an effort to establish a comprehensive validation framework. A main element is a transformation model of point-to-area rainfall which is experimentally verified. The findings of this research have implications for the use of radar-rainfall data in applications such as hydrologic modeling, flood forecasting, numerical weather prediction models, and validation of other remote sensing rainfall estimates, among others.

  3. Improvement of X-band radar rainfall estimates using a microwave link

    NASA Astrophysics Data System (ADS)

    Krämer, S.; Verworn, H.-R.; Redder, A.

    2005-09-01

    In recent years the significance of highly resolved rainfall information in space and time for hydrological applications increased steadily. Weather radar systems provide this information but the derivation of quantitatively reliable radar rainfall estimates is still known to be problematic. The attenuation of the radar signal by rainfall has been identified as crucial and especially X-band radars are affected by this phenomenon. The current methods of correcting for attenuation face many problems, mainly because the actual amount of attenuation is unknown. In this paper attenuation and rainfall information derived from a microwave link are used as a reference to correct an X-band radar for rainfall. A microwave link receiver is co-located with an X-band weather radar in Essen, Germany. Therefore, the microwave link provides path integrated attenuation and rainfall information parallel to a radar beam over a distance of 30 km. The correction of radar rainfall is done in two steps: first, the radar data are corrected for attenuation and in a second step the microwave link derived rainfall is used together with information obtained from distrometer data to calculate the rainfall from the corrected radar reflectivities. A network of twelve rain gauges located in the vicinity of the link path provide a measure of the 'ground truth' rainfall. It is shown that the microwave link gives valuable information to improve the radar rainfall estimates of the X-band radar.

  4. 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).

  5. Aggregation and disaggregation of radar rainfall rates

    NASA Astrophysics Data System (ADS)

    Krebsbach, K.; Friederichs, P.

    2012-12-01

    Spatially distributed, high-resolution precipitation rates are key ingredients for modeling soil-vegetation processes, water and solute transports in mesoscale catchments, and for short-range weather prediction. The ultimate goal of our study is to develop a space-time, multilevel statistical model that merges rain radar measurements with other observations of precipitation. This is a challenging task since it aims at combining data sources with a variety of error structures, and temporal resolutions. E.g., in-situ measurements are quite accurate, but available only at sparse and irregularly distributed locations, whereas remote measurements cover complete areas but suffer from spatially and temporally inhomogeneous systematic errors. The first step towards such a space-time precipitation model is to develop a statistical model for precipitation based on radar measurements. Precipitation rates over a region of about 230× 230 km2 are provided by a composite of the two polarimetric X-band radars in Germany. The two radars are located in a distance of about 60 km in Bonn and Jülich, respectively. For the statistical model formulation we use a Gaussian Markov random field as underlying process. A Markov random field is a suitable model to account for spatial dependencies if the neighborhood can be reduced to a small region without losing information. This makes large data problems computationally feasible, since the neighborhood structure is given by a sparse precision matrix. Markov random fields are closely related to a graphical models. In processing the unadjusted radar rainfall rates, we follow D. Allcroft and C. Glasbey (2003)footnote{⪉bel{foot:1}David Allcroft and Chris Glasbey (2003). A latent Gaussian Markov Random Field model for spatiotemporal rainfall disaggregationJournal of the Royal Statistical Society: Series C (Applied Statistics), 52:487-498}. We start with a transformation of the precipitation rates to a truncated Gaussian distribution. The advantage of such a latent variable approach is that the occurrence as well as the intensity of rainfall are modeled by a single spatial process. The correlation function is then estimated as a function of the lag distance in space (and time) using the maximum likelihood method. Finally the Gaussian Markov random field is fitted such that its inverse is close to the empirical covariance matrix in some matrix norm. Therefore we use a minimum least squares method and implement a penalty term to assure the positive definiteness of the resulting covariance matrix. Note, that throughout our calculations we assume stationarity. The statistical model then allows for a disaggregation and aggregation of precipitation rates.

  6. 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.

  7. 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

  8. 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…

  9. GIS Based Stereoscopic Visualization Technique for Weather Radar Data

    NASA Astrophysics Data System (ADS)

    Lim, S.; Jang, B. J.; Lee, K. H.; Lee, C.; Kim, W.

    2014-12-01

    As rainfall characteristic is more quixotic and localized, it is important to provide a prompt and accurate warning for public. To monitor localized heavy rainfall, a reliable disaster monitoring system with advanced remote observation technology and high-precision display system is needed. To advance even more accurate weather monitoring using weather radar, there have been growing concerns regarding the real-time changes of mapping radar observations on geographical coordinate systems along with the visualization and display methods of radar data based on spatial interpolation techniques and geographical information system (GIS). Currently, the method of simultaneously displaying GIS and radar data is widely used to synchronize the radar and ground systems accurately, and the method of displaying radar data in the 2D GIS coordinate system has been extensively used as the display method for providing weather information from weather radar. This paper proposes a realistic 3D weather radar data display technique with higher spatiotemporal resolution, which is based on the integration of 3D image processing and GIS interaction. This method is focused on stereoscopic visualization, while conventional radar image display works are based on flat or two-dimensional interpretation. Furthermore, using the proposed technique, the atmospheric change at each moment can be observed three-dimensionally at various geological locations simultaneously. Simulation results indicate that 3D display of weather radar data can be performed in real time. One merit of the proposed technique is that it can provide intuitive understanding of the influence of beam blockage by topography. Through an exact matching each 3D modeled radar beam with 3D GIS map, we can find out the terrain masked areas and accordingly it facilitates the precipitation correction from QPE underestimation caused by ground clutter filtering. It can also be expected that more accurate short-term forecasting will be possible using stereoscopic observation of weather phenomena changes.

  10. 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 'Talas' of 2011 over the two catchments, which are Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments of Shingu river basin (2360 km2), which is located in the Kii peninsula, Japan.

  11. 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.

  12. 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 hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF, 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 M, 2009. High-resolution precipitation estimates for hydrological uses. Proceedings of the Institution of Civil Engineers - Water Management 162: 125-135.

  13. 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...

  14. Dual Multiparameter Radar Observation of Rainfall: Application of Tomographic Technique

    NASA Astrophysics Data System (ADS)

    Dobaie, Abdullah M.

    1995-01-01

    Since the advent of the multiparameter weather radar, i.e., dual-polarization, dual-frequency, and Doppler radar, radar meteorologists have been able to study physical process in precipitation in more detail, and the quantitative measurements of rainfall has become possible. Specific differential propagation phase (K_{DP }) is a useful measurement for estimation of rainfall specially at high rainrates. K_ {DP} is obtained as the range derivative of phi_{DP} and is proportional to the mean difference in forward scatter amplitudes of raindrops in the resolution volume. It has been studied that rainfall rate estimation based on K _{DP}, R(K_{DP}), is more accurate than rainfall estimate based on Z_{H}, R(Z_{H }), and rainfall estimate based on both Z _{H} and Z_{DR }, R(Z_{H}, Z_ {DR}), especially, at high rainfall rate ({>}80 mmh^{-1}). . In this research we introduce a promising technique to estimate the two-dimensional spatial distribution of K_{DP} based on observations from two dual polarization radars, and then use the K _{DP} - R powerlaw relation to estimate the rainfall rate. A modification of the conventional tomographic reconstruction procedure is used to reconstruct K_{DP} field using phi_{DP} profiles from two dual polarized radars. A numerical simulation for the proposed tomographic method is introduced. The concept of averaging of staggered common monitored areas resulted in a good agreement with the distribution field of the simulated K_{DP}. An error analysis has been done for the reconstructed parameter and a standard deviation for the reconstructed K _{DP} field (sigma _{k_{DP}}) of 0.2 degkm^{-1} is achieved as a result of 4^circ standard deviation of the measured phi_{DP }. The tomographic method developed in this research is applied to the multiparameter data from July 13, 1993 storm event that occurred near Longmont, Colorado.

  15. 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.

  16. 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 differential reflectivity and Doppler as functions of the center frequency, frequency difference, and median mass diameter. For a fixed pair of frequencies, the detectability of the differential signals can be expressed as the number of independent samples required to detect rain or snow with a particular median mass diameter. Because sampling numbers on the order of 1000 are needed to detect the differential signal over a range of size distributions, the instrument must be confined to a near-nadir, narrow swath. Radar measurements from a zenith directed radar operated at 9.1 GHz and 10 GHz are used to investigate the qualitative characteristics of the differential signals. Disdrometer and rain gauge data taken at the surface, just below the radar, are used to test whether the differential signals can be used to estimate characteristics of the raindrop size distribution.

  17. On the Propagation of Radar-rainfall Estimation Uncertainties Into the Simulation of Different Rainfall-runoff Processes

    NASA Astrophysics Data System (ADS)

    Habib, M. A.; Habib, E. H.; Vitla, V.

    2007-12-01

    Recent advances in remote sensing of rainfall provide unprecedented opportunities for acquiring rainfall measurements with high spatial and temporal resolutions. In particular, the Next Generation Weather Radar (NEXRAD) system is a promising resource for improving the accuracy and reliability of hydrologic predictions and operational forecasting. However, rainfall estimates from radar measurements are subject to uncertainties caused by both instrumental effects and lack of unique relation between radar-rainfall estimations and the surface rainfall quantities. The effect of such uncertainties on the predictive ability of hydrologic models is an active area of research. This study will investigate the propagation of radar-rainfall estimation uncertainties into the simulation of different rainfall-runoff processes. The analysis is performed over a mid-size watershed that is heavily monitored by a dense network of rainfall and streamflow gauges. The study uses a physically-based distributed hydrological model (Gridded Surface Subsurface Hydrologic Analysis, GSSHA). The model will be calibrated and validated using several historical rainfall-runoff storms. Radar estimation errors will be first assessed in terms of their marginal error distribution and spatial and temporal auto-correlations. Then, radar- based runoff simulations will be assessed in comparison to simulations using data from the dense rain gauge network in the watershed. The study will examine the effect of radar-rainfall uncertainties on simulations of various processes such as infiltration, surface runoff, soil moisture, and streamflow. Then, a simulation-based stochastic model for the radar error will be developed based on its identified characteristics (i.e., marginal distribution and spatio-temporal correlations). This model will provide a tool for generating multiple realizations of the radar error field and enable examination of the probabilistic nature of the error propagation into runoff predictions.

  18. 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.

  19. Research relative to weather radar measurement techniques

    NASA Astrophysics Data System (ADS)

    Smith, Paul L.

    1992-08-01

    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.

  20. Radar rainfall estimation for the identification of debris-flow precipitation thresholds

    NASA Astrophysics Data System (ADS)

    Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco

    2014-05-01

    Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial variogram) of the triggering rainfall. These results show that weather radar has the potential to effectively increase the accuracy of rainfall thresholds for debris flow occurrence. However, these benefits may only be achieved if the same monitoring instrumentation is used both to derive the rainfall thresholds and for use of thresholds for real-time identification of debris flows occurrence. References Nikolopoulos, E.I., Borga M., Crema S., Marchi L, Marra F. & Guzzetti F., 2014. Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris-flow occurrence. Geomorphology (conditionally accepted) Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C., and Guzzetti, F., 2012. Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy, Geomorphology, 139-140, 79-90, 2012.

  1. 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 'singularities' of radar rainfall fields and preserves them throughout the merging process (Wang and Onof, 2013). Singularities are defined through the fact that the areal average rainfall increases as a power function when the area decreases (Cheng et al., 1994). In the proposed methodology singularities are first identified and extracted from the radar rainfall field. The resulting non-singular radar field is then used in the merging process and the singularities are subsequently and proportionally added back to the final reconstructed rainfall field. A full-scale testing of this methodology in an urban area in the UK has been conducted and the result suggests that the original Bayesian data merging technique (Todini, 2001) could be effectively improved by incorporating this singularity analysis. References Cheng, Q., et al., (1994) Journal of Geochemical Exploration, 51(2), 109-130. Todini, E., (2001) Hydrology and Earth System Sciences, 5, 187-199. Wang, L. et al., (2013) Water Science & Technology, 68(4), 737-747. Wang, L. and Onof, C., (2013) Hydrofractals '13, Kos island, Greece.

  2. 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 model has good performances in simulating the outflows of seven historical typhoon events. With the proposed flood prediction model, it can be coupled with flow routing and sediment transport models to develop a warning system for bridge damage in downstream of Dajia River.

  3. Tests of Radar Rainfall Retrieval Algorithms

    NASA Technical Reports Server (NTRS)

    Durden, Stephen L.

    1999-01-01

    The NASA/JPL Airborne Rain Mapping Radar (ARMAR) operates at 14 GHz. ARMAR flew on the NASA DC-8 aircraft during Tropical Ocean Global Atmosphere (TOGA) Coupled Ocean Atmosphere Response Experiment (COARE), collecting data in oceanic mesoscale convective systems, similar to those now being observed by the Tropical Rainfall Measuring Mission (TRMM) satellite, which includes a 14-GHz precipitation radar. Several algorithms for retrieving rain rate from downward looking radars are in existence. These can be categorized as deterministic and stochastic. Deterministic algorithms use the path integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the attenuation-rainfall (k-R) relation, while another corrects the reflectivity rainfall (ZR) relation. Stochastic algorithms apply an Extended Kalman Filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. We find that the stochastic algorithm with 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. The underestimation is illustrated in the diagram. The algorithm labeled D IS initially assumes a DSD that is appropriate for stratiform. rain, while the rain is most likely convective. The PIA constraint causes the k-R relation to be adjusted, resulting in a much lower rain rate than the other algorithms. Additional information is contained in the original.

  4. 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.

  5. 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 using standard frequency analysis techniques, are important controls on flood response. We compare the results of SST-based flood frequency analyses to peak streamflow observations and to the results of other frequency analysis techniques.

  6. 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.

  7. Terminal Doppler weather radar clutter control

    NASA Astrophysics Data System (ADS)

    Evans, James E.; Drury, William H.; Hynek, Daniel P.; Lee, T. Sen; Stevens, B. H., Jr.

    A number of unique approaches to clutter rejection which have been validated with the terminal Doppler weather radar (TDWR) testbed radar are described. Key aspects of the detection problem are emphasized from the viewpoint of a radar engineer (as opposed to the meteorological and pattern recognition features of the problem). Attention is focused on mainlobe clutter suppression since it is a principal cause of inadequate detection performance. To provide a framework for the TDWR system discussions, the salient features of the low-altitude wind shear detection environment and the pattern recognition algorithms are first described. Some of the system features which arise from ground clutter suppression considerations are then discussed. Clutter due to out-of-trip weather returns is also an important factor in TDWR system engineering due to the tradeoff between unambiguous velocity and range (coupled with the (range)-2 power law for weather echoes). Some of the radar engineering areas which warrant additional investigation are discussed.

  8. Spaceborne Radar Measurements of Rainfall Vertical Velocity

    NASA Technical Reports Server (NTRS)

    Im, Eastwood; Tanelli, Simone; Giuli, Dino; Durden, Stephen L.; Facheris, Luca

    2000-01-01

    This paper studies the performance of a spaceborne precipitation radar in measuring vertical Doppler velocity of rainfall. As far as a downward pointing precipitation radar is concerned, one of the major problems affecting Doppler measurement at the nadir direction arises from the Non-Uniform Beam-Filling effect (NUBF). That is, when significant variation in rain rate is present within the radar IFOV (Instrument Field of View) in the along track direction. the Doppler shift caused by the radial component of the horizontal speed of the satellite is weighted differently among the portions of IFOV. The effects of this non-uniform weighting may dominate any other contribution. Under this condition, shape, average value and width of the Doppler spectrum may not be directly correlated with the vertical velocity of the precipitating particles. However, by using an inversion technique which over-samples the radar measurements in the along track direction, we show that the shift due to NUBF can be evaluated, and that the NUBF induced errors on average fall speed can be reduced.

  9. Radar rainfall estimation as an optimal prediction problem

    NASA Astrophysics Data System (ADS)

    Ciach, Grzegorz Jan

    A formulation of the radar rainfall estimation problem as optimal statistical prediction of area-averaged rainfall accumulations based on the radar measured reflectivity is presented. Questions of the estimation and validation of such optimal prediction procedures based on large samples of synchronous radar and raingage measurement are analyzed. Our approach accepts the truth that radar cannot mimic the near-point raingage sampling and that proper quantification of the area-point difference is necessary. The questions and consequences which originate from our formulation of the radar rainfall estimation/validation problem are formalized statistically and investigated using both statistical modeling and data analysis. A general definition of the error of the radar rainfall predictions in terms of bivariate probability distributions of the radar and true rainfalls is discussed. The raingage representativeness error structure is analyzed based on the available data. An analytically tractable statistical model of the radar-raingage comparisons is developed. It shows the large impact of the estimation method on the resulting reflectivity-rainrate conversion and the incompleteness of the system due to the radar and raingage errors. These effects prove the need of additional data on the raingage area-point difference structure. Next, an Error Separation Method for the error variance estimation of the radar rainfall predictions is developed. This method is based on additional data on the rainfield small scale correlation structure. Finally, a global optimization approach to the multiparameter radar rainfall prediction is developed. The prediction algorithm is designed to minimize the error variance of the final radar rainfall product. The general radar rainfall estimation/validation methodologies developed here can also be applied to other remote sensing rainfall estimation problems. The work is concluded with a summary discussion of the obtained results and of the research directions that might stem from those results.

  10. A New Approach For Reducing The Uncertainty In Radar Rainfall Estimation Procedures

    NASA Astrophysics Data System (ADS)

    Chumchean, S.; Sharma, A.

    The weather radar provides a convenient means for measuring rainfall in space and time. However, its use as a rainfall measuring device is limited due to the poor accu- racy of algorithms used to convert the measured reflectivity to ground rainfall. While this accuracy can be acceptable in situations where the catchment is large and ground measurements few, the use of radar based rainfall observations can lead to signifi- cant errors in small catchments located far from the radar site. This study aims to identify some of the reasons behind the limited accuracy of radar rainfall estimation algorithms, and proposes a method that addresses some of the factors responsible. The accuracy of weather radars is effected by a number of factors, not all of which are considered in the algorithms used. Some of these are: (a) mis-specification of the relationship between reflectivity and rainfall through the use of an improperly speci- fied equation, (b) nonstationarity in measured reflectivity values due to changes in the rainfall drop size distribution, (c) an inability to convert the reflectivity measured at an elevation above ground to the rainfall at ground level, and, (d) a reduction in the reli- ability associated with measured reflectivity with increase in distance from the radar, a result of the radar emitted power being shared over an increasing volume of air. The above factors can be addressed by either formulating a relationship that is stable and consistent, or using a quantile matching approach called the Probability Matching Method (PMM) which is helpful when the relationship is difficult to specify. How- ever, for either method to be useful, the measured reflectivity must be stationary, or, must bear the same relation with rainfall irrespective of factors such as changes in storm type or distance from the radar. Another cause of nonstationarity in the mea- sured reflectivity values is use of measurements that vary in accuracy depending on their distance from the radar site. As conventional methods do not attempt to take ac- count of the factors mentioned, the resulting algorithms are uncertain and unstable, and perform poorly especially when applied to storms not used in the calibration ex- ercise. Presented here is an approach that attempts to identify and correct for known sources of nonstationarity in radar reflectivity observations, and establish a procedure that explicitly takes into account the variations in reliability associated with the ob- servations used. This approach is applied to six months of reflectivity values from the Kurnell radar in Sydney, Australia.

  11. 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.

  12. 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....

  13. 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....

  14. 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....

  15. 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....

  16. 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....

  17. 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 library together with a few showcase examples.

  18. 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.

  19. Empirically-based modeling of radar-rainfall uncertainties

    NASA Astrophysics Data System (ADS)

    Villarini, Gabriele

    There are large uncertainties associated with radar-based rainfall estimates, including both systematic errors and random effects from numerous sources. Their propagation through all models for which radar-rainfall is used as input or for which is used as an initial condition is necessary to enhance our understanding and interpretation of the obtained results. Despite the relevance of the topic, there is no comprehensive statistical characterization of these errors. The specific goals of this dissertation include: (1) development of an empirically-based radar-rainfall error model; (2) investigation of the sensitivity of the components of the error model to different radar setups, spatial and temporal resolutions, and geographic areas; (3) development of a generator of ensembles of probable true rainfall fields, conditioned on a given radar-rainfall map; (4) application of the error model to: (i) the flash flood forecasting problem; (ii) the evaluation of satellite-based rainfall products; and (iii) the impact of radar-rainfall uncertainties on the scaling properties of rainfall; According to the approach proposed in this study, a realistic parameterization of the relationship between true rainfall and radar-rainfall can be achieved with a model described by two elements: a systematic distortion function and a random component. These two components are identified using a non-parametric approach, and rain gauges are used as an approximation of the true ground rainfall. This model has the flexibility to account for range from the radar, different spatio-temporal scales, rain regime, and space and time dependency of the errors. The results of this study are based on large samples of radar and rain gauge data from Oklahoma, United States, and south-west Great Britain. One of the assumptions in this study is that the true ground areal rainfall can be approximated by rain gauge measurements, introducing sampling discrepancies between a radar pixel and a rain gauge. Therefore, the uncertainties associated with the approximation of an areal estimate with a point measurement (spatial sampling errors) will be investigated for different spatial and temporal scales by means of an empirically-based error model.

  20. 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.

  1. 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 distribution of rain intensity in higher resolution by using only the information of the hourly radar data and an assumed temporal distribution of rainfall at each radar grid cell. The methods preserves the total rainfall amount at each cell and preserves the overall rainfall pattern and movement of precipitation cells. Generally, we could improve the prediction of the model for short convective events in particular for the peak discharge. The higher temporal resolution effects the runoff generation and depends strongly on soil characteristics. On soils with high infiltration capacity the increase of temporal resolution effects the generation of fast overland runoff. This effect decreases with decreasing infiltration capacity of soils. The analysis revealed that a variable temporal resolution is needed to model convective and advective rainfall events with the same model parameterization. A "correct" spatial resolution of the distributed model, however, depends strongly on the dominant runoff generation process in a watershed and is also different for runoff generation and runoff concentration.

  2. 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

    This communication is about a methodology for radar rainfall estimation in the context of post-event analysis of flash-flood events developed within the HYDRATE project. For such extreme events, some raingauge observations (operational, amateur) are available at the event time scale, while few raingauge time series are generally available at the hydrologic time steps. Radar data is therefore the only way to access to the rainfall space-time organization, but the quality of the radar data may be highly variable as a function of (1) the relative locations of the event and the radar(s) and (2) the radar operating protocol(s) and maintenance. A positive point: heavy rainfall is associated with convection implying better visibility and lesser bright band contamination compared with more current situations. In parallel with the development of a regionalized and adaptive radar data processing system (TRADHy; Delrieu et al. 2009), a pragmatic approach is proposed here to make best use of the available radar and raingauge data for a given flash-flood event by: (1) Identifying and removing residual ground clutter, (2) Applying the "hydrologic visibility" concept (Pellarin et al. 2002) to correct for range-dependent errors (screening and VPR effects for non-attenuating wavelengths, (3) Estimating an effective Z-R relationship through a radar-raingauge optimization approach to remove the mean field bias (Dinku et al. 2002) A sensitivity study, based on the high-quality volume radar datasets collected during two intense rainfall events of the Bollène 2002 experiment (Delrieu et al. 2009), is first proposed. Then the method is implemented for two other historical events occurred in France (Avène 1997 and Aude 1999) with datasets of lesser quality. References: Delrieu, G., B. Boudevillain, J. Nicol, B. Chapon, P.-E. Kirstetter, H. Andrieu, and D. Faure, 2009: Bollène 2002 experiment: radar rainfall estimation in the Cévennes-Vivarais region, France. Journal of Applied 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.

  3. Radar rainfall accumulation estimation and nowcasting for real time flood warning

    NASA Astrophysics Data System (ADS)

    Burton, A.; Hannesen, R.; O`Connell, P. E.

    2003-04-01

    The EC project MUSIC (EVK1-CT-2000-00058) aims to develop a flood warning system to support operational decisions for the reduction of flood risk. An important component will be a rainfall nowcasting facility, whereby the location and intensity of rainfall is forecast for up to 6 hours ahead with a spatial resolution of about 2km. The characteristics of rainfall forecasts estimated using Numerical Weather Prediction are such that a direct forecast based on rainfall observations using a simple model can achieve a higher skill score for a short period, of the order of 4 hours. This is the aim of the MUSIC rainfall nowcasting system. Existing methodologies quantify the present precipitation state in terms of statistical properties or feature identification. They then achieve the forecasting step by extrapolating state variables (often using auto regressive models or artificial neural networks) and have sometimes used additional data from satellite observations or numerical weather prediction. Similarly, the method applied here is to decompose a radar image into features which are then tracked from one image to the next using an object-orientated methodology. The tracking uses lag-correlation to estimate velocity with a highly efficient algorithm. A number of alternative formulations of the forecasting step will be described. The interface between rainfall estimation and rainfall-runoff modelling will also be considered. Rainfall-runoff models typically use rainfall data which is accumulated in time. When intense precipitation features move with a high velocity in the time interval between radar scans, care must be taken to ensure that accumulation estimates are free from errors caused by the discrete nature of radar scans. The accumulation component within the MUSIC system addresses this issue.

  4. 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 and depth records. The results show that the temporally-interpolated rainfall estimates can better reproduce the small-scale dynamics of the storm events, leading to better reproduction of urban runoff.

  5. 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.

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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.

  12. 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. ...

  13. Weather radar to prevent air crashes

    NASA Astrophysics Data System (ADS)

    Bush, Susan M.

    An operational demonstration of Terminal Doppler Weather Radar (TDWR) at Stapleton International Airport, Denver, finishes August 31. For 2 months, TDWR has been used to detect wind shear and other hazardous weather around air terminals and to provide warnings to air traffic controllers and pilots in time to avert accidents.The biggest hazard for aircraft approaching or departing terminals is the microburst, a form of wind shear. Microbursts are produced by a small-scale, powerful downdraft of cold, heavy air occurring beneath a thunderstorm, rain shower, or cumulus cloud. As the downdraft reaches Earth's surface, it spreads out horizontally (see Figure 1). An aircraft flying through a microburst at low-altitude encounters a strong headwind, then a downdraft, and finally a tailwind that causes a sharp reduction in speed and loss of lift. This deadly sequence of events has caused at least 30 accidents and 500 deaths in the United States since the mid-1960s.

  14. 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 Gini index, Rosenbluth index) were calculated and compared to the synoptic situation in general and the atmospheric stability in special. The indices were then related to the drop size distributions and the rain rate. Special emphasis was laid in an objective distinction between stratiform and convective precipitation and hereby altered droplet size distribution, respectively Z/R relationship. In our presentation we will show how convective and stratiform precipitation becomes manifest in the different distribution indices, which in turn are thought to represent different patterns in the radar image. We also present and discuss the correlation between these distribution indices and the evolution of the drop size distribution and the rain rate and compare a dynamically adopted Z/R relation to the standard Marshall-Palmer Z/R relation.

  15. Nonlinear estimation of monsoon rainfall from radar and raingage data

    NASA Technical Reports Server (NTRS)

    Krajewski, Witold F.; Lin, Dah-Syang

    1989-01-01

    Estimates of climatological rainfall are made as part of the validation program for the Tropical Rainfall Measuring Mission. Radar and raingage data collected during AMEX in Darwin, Australia during 1987 and 1988 are analyzed using a nonlinear merging methodology known as disjunctive cokriging (Azimi-Zonooz et al., 1989). The methodology is outlined and the results are used to determine the most advantageous time scale for estimation.

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. Stochastic simulation experiment to assess radar rainfall retrieval uncertainties associated with attenuation and its correction

    NASA Astrophysics Data System (ADS)

    Uijlenhoet, R.; Berne, A.

    2008-03-01

    As rainfall constitutes the main source of water for the terrestrial hydrological processes, accurate and reliable measurement and prediction of its spatial and temporal distribution over a wide range of scales is an important goal for hydrology. We investigate the potential of ground-based weather radar to provide such measurements through a theoretical analysis of some of the associated observation uncertainties. A stochastic model of range profiles of raindrop size distributions is employed in a Monte Carlo simulation experiment to investigate the rainfall retrieval uncertainties associated with weather radars operating at X-, C-, and S-band. We focus in particular on the errors and uncertainties associated with rain-induced signal attenuation and its correction for incoherent, non-polarimetric, single-frequency, operational weather radars. The performance of two attenuation correction schemes, the (forward) Hitschfeld-Bordan algorithm and the (backward) Marzoug-Amayenc algorithm, is analyzed for both moderate (assuming a 50 km path length) and intense Mediterranean rainfall (for a 30 km path). A comparison shows that the backward correction algorithm is more stable and accurate than the forward algorithm (with a bias in the order of a few percent for the former, compared to tens of percent for the latter), provided reliable estimates of the total path-integrated attenuation are available. Moreover, the bias and root mean square error associated with each algorithm are quantified as a function of path-averaged rain rate and distance from the radar in order to provide a plausible order of magnitude for the uncertainty in radar-retrieved rain rates for hydrological applications.

  2. 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, leading to a dynamic weighting scheme. The weighted combination method reduces the MSE by close to 50% compared to a traditional power law method for using the radar reflectivity. The combined method has the lowest overall error of the three methods over the densely gauged Sydney region.

  3. 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.

  4. 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.

  5. National Weather Service

    MedlinePlus

    HOME FORECAST Local Graphical Aviation Marine Rivers and Lakes Hurricanes Severe Weather Fire Weather Sun/Moon Long ... Policy LOADING... ACTIVE ALERTS FORECAST MAPS RADAR RIVERS, LAKES, RAINFALL AIR QUALITY SATELLITE PAST WEATHER American Samoa ...

  6. 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.

  7. 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.

  8. 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.

  9. 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).

  10. 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.

  11. Hydro-NEXRAD radar database: A community resource for rainfall studies

    NASA Astrophysics Data System (ADS)

    Kruger, A.; Krajewski, W. F.; Goska, R.; Domaszczynski, P.; Gunyon, C.; Smith, J. A.; Baeck, M. L.

    2009-04-01

    Hydro-NEXRAD is a software system with web-based user interface for obtaining historical customized NEXRAD-based radar-rainfall maps (products) from some 40 WSR-88D radars covering mainly the central and eastern U.S. These products have increased spatial and temporal resolution in comparison to the operational products available from the US National Weather Service. Rainfall researchers and hydrologists can request customized products by selecting various algorithmic modules and parameter values. The produced rainfall maps can be projected on a grid of choice. The output is formatted for ingest by geographic information systems and mapping software. The authors present the system architecture, the database extent and the possibilities of including additional algorithms in the future versions. They illustrate the utility of the software with several applications where side-by-side comparisons of various products allow studies of uncertainty propagation and sensitivity analysis. One of the comparisons presented involves the NWS products obtained with the Precipitation Processing System. Since one of the features of Hydro-NEXRAD is repeatability of the results, the system promotes systematic studies of new algorithms, comparisons with rain gauge data and error modeling, and uncertainty propagation in hydrologic applications. The system can be considered as prototype of large-scale data dissemination system broadly customized for a specific application. The system could be evolved into a world-wide database of radar data serving the needs of global remote sensing research community.

  12. Architectures for Rainfall Property Estimation From Polarimetric Radar

    NASA Astrophysics Data System (ADS)

    Collis, S. M.; Giangrande, S. E.; Helmus, J.; Troemel, S.

    2014-12-01

    Radars that transmit and receive signals in polarizations aligned both horizontal and vertical to the horizon collect a number of measurements. The relation both between these measurements and between measurements and desired microphysical quantities (such as rainfall rate) is complicated due to a number of scattering mechanisms. The result is that there ends up being an intractable number of often incompatible techniques for extracting geophysical insight. This presentation will discuss methods developed by the Atmospheric Measurement Climate (ARM) Research Facility to streamline the creation of application chains for retrieving rainfall properties for the purposes of fine scale model evaluation. By using a Common Data Model (CDM) approach and working in the popular open source Python scientific environment analysis techniques such as Linear Programming (LP) can be bought to bear on the task of retrieving insight from radar signals. This presentation will outline how we have used these techniques to detangle polarimetric phase signals, estimate a three-dimensional precipitation field and then objectively compare to cloud resolving model derived rainfall fields from the NASA/DoE Mid-Latitude Continental Convective Clouds Experiment (MC3E). All techniques show will be available, open source, in the Python-ARM Radar Toolkit (Py-ART).

  13. 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 estimation of the CASA DFW QPE system, rainfall measurements from ground rain gauges will be used for evaluation purposes. This high-resolution QPE system is used for urban flash flood forecasting when coupled with hydrological models.

  14. 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.

  15. 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-arid climatic transition.

  16. Rainfall: From Fractals to Multifractals, From Weather to Climate

    NASA Astrophysics Data System (ADS)

    Tchiguirinskaia, I.; Schertzer, D. J.; Fitton, G. F.; Gires, A.

    2013-12-01

    The Intensity-Duration-Frequency (IDF) curves are a classical example of statistical models relating weather and climate time scales. There are numerous standard IDF models. Whereas these parametric models yield similar values near the centre of the distribution, because they are fitted on low order statistics, the extreme quantiles often differ significantly. Unfortunately, these models are based on hypotheses opposite to the long-range dependencies, non-stationarity and clustering of the extremes displayed by rainfall. Searching for methods that could bridge weather and climate time scales of the IDF curves but incorporating physical principles, there have been numerous applications of scaling theories during the last decade. The majority of available theoretical results concerning the scaling extrapolation of the IDF curves has been obtained either with the help of a ';simple scaling' formalism or the multifractal formalism. While the former oversimplifies a multifractal nature of rainfall, the latter often assumes a strict equivalence between the duration (of a sliding window for moving average) and the scale of data observation (corresponding to disjoint windows). In a general manner, the scaling behavior of IDF curves strongly depends on how the durations are defined. An additional complexity arises from the fact that zero-rainfall generally introduces a scaling break between small and large time scales of the rainfall process. In this presentation we discuss the real scaling nature of the rainfall, the nonlinear transformations associated to scaling and duration changing, including for the climate-relevant return periods that very often exceed the length of available historical records. For this purpose, we use a procedure recently developed for near-wall atmospheric turbulence to define conservative flux proxies from empirical data such that they correspond to well-defined stochastic multiplicative processes in the framework of a nonlinear generalized scale invariance. This extends the scaling range of the empirical data and thus leads to non-ambiguous estimates of the universal multifractal parameters. This procedure has been tested on numerous rainfall data. The results explain why over past decades there have been numerous, unsuccessful attempts of modeling the rainfall process as a product of a stochastic multifractal with a fractal field generating the zero rainfall, whereas the rainfall process does not correspond to a passive scalar or a conservative flux, but to a fractionally integrated flux.

  17. Reconstruction of reflectivity vertical profiles and data quality control for C-band radar rainfall estimation

    NASA Astrophysics Data System (ADS)

    Fornasiero, A.; Alberoni, P. P.; Vulpiani, G.; Marzano, F. S.

    2005-06-01

    Microwave Doppler radars are considered a fairly established technique to retrieve rain rate fields from measured reflectivity volumes. However, in a complex orographic environment radar observations are affected by several impairments which should be carefully evaluated. Together with the enhancement of ground-clutter effects, the major limitation is represented by partial or total beam blocking caused by natural obstructions which very often impose to scan at high-elevation angles. These range-related limitations tend to reduce the potential role of operational weather radars in monitoring precipitation amount at ground within mountainous areas since, if either the nature or intensity of rainfall varies with height (e.g., melting effects during stratiform rain), radar returns at higher altitudes may be not representative of surface rain rate. Therefore, before to use the radar data, it is necessary to reduce, as much as possible, this evaluation errors and to estimate the reliability of the processed data. Near to the quality control, are needed quality indexes, taking into account each correction and elaboration step, that could be useful to retrieve a final quality value. In this work, we analyse the main factors that could be affect the efficiency of a reconstruction methodology of near-surface reflectivity fields from high-elevation reflectivity bins, in presence of complex orography. A climatologic schema is applied to infer near-surface reflectivity at a given range interval. The technique is developed in polar coordinates partially taking into account the antenna beam width degradation at longer ranges and overall computational efficiency for operational purposes. Thereafter, it is applied on a rainfall event observed by a C-band Doppler radar operating in S. Pietro Capofiume (Bologna, Italy) and the relation between the reconstruction error and possible quality indicators is analysed and discussed.

  18. 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.e. the observed scaling factors C(xα)) on a distance aαK by introducing an offset parameter K, which results in slightly different equations to calculate a and a0. The described technique is currently being used by the Flemish Environmental Agency in an online forecasting system of river discharges within Flanders (Belgium). However, rescaling the radar data using the described algorithm is not always giving rise to an improved weather radar product. Probably one of the main reasons is the parameters K and ? which are implemented as constants. It can be expected that, among others, depending on the characteristics of the rainfall, different values for the parameters should be used. Adaptation of the parameter values is achieved by an online calibration of K and ? at each time step (every 15 minutes), using validated rain gauge measurements as ground truth. Results demonstrate that rescaling radar images using optimized values for K and ? at each time step lead to a significant improvement of the rainfall estimation, which in turn will result in higher quality discharge predictions. Moreover, it is shown that calibrated values for K and ? can be obtained in near-real time. References Cole, S. J., and Moore, R. J. (2008). Hydrological modelling using raingauge- and radar-based estimators of areal rainfall. Journal of Hydrology, 358(3-4), 159-181. Hardy, R.L., (1971) Multiquadric equations of topography and other irregular surfaces, Journal of Geophysical Research, 76(8): 1905-1915. Moore, R. J., Watson, B. C., Jones, D. A. and Black, K. B. (1989). London weather radar local calibration study. Technical report, Institute of Hydrology.

  19. 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.

  20. 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

  1. 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.

  2. Mapping Wintering Waterfowl Distributions Using Weather Surveillance Radar

    PubMed Central

    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

  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. Comprehensive Testing and Evaluation of the Hydro-NEXRAD Multiple Radar-Rainfall Algorithms

    NASA Astrophysics Data System (ADS)

    Seo, B.; Krajewski, W. F.

    2008-05-01

    Ordinary approaches to quantitatively estimate radar rainfall are based on single radar rainfall processing. Sometimes, limited coverage and beam geometry problems (e.g. blockage and vertical gaps) prevent using single radar data for hydrologic and atmospheric applications. Some of those restrictions can be mitigated by combining data from two or more radars. Merging multiple radar data enables studies that need to cover larger hydrologic units represented by watersheds or basins. However, numerous challenges associated with temporal and spatial synchronization, as well as calibration differences among WSR-88Ds, still remain to be solved. The Hydro-NEXRAD multiple radar rainfall estimation algorithms include two options: (1) data-based merging; and (2) product-based merging. Data-based merging takes reflectivity data from all radars involved through preprocessing algorithm that performs volume scan data quality control, interpolates data to synchronize temporal scale between individual radars, and finally combines data onto a common geographic grid. Reflectivity values for a given location are assigned by a weighting function with respect to the distance from the radar. This single reflectivity field is then converted to rainfall amounts using a user-requested standard approach. In product-based merging reflectivity data from multiple radars are all converted to rainfall using the same, user- specified algorithm. These products are then combined into the final one using a weighting function that expresses the uncertainty of estimated rainfall amounts. The uncertainty model used accounts for effects of range from radar, and rainfall amount. The authors present comprehensive testing and comparison results for the Hydro-NEXRAD rainfall estimates. They evaluate the Hydro-NEXRAD products with another multiple radar rainfall estimates (no bias removal) from National Center for Environmental Prediction, operational NEXRAD products (Stage III) from regional River Forecast Centers, and rain gauge data. The results show that more sophisticated algorithms that account for range correction and other improvements lead to better performance of the multiple radar rainfall estimates.

  6. 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.

  7. The Next Generation Weather Radar (NEXRAD)/Air Route Surveillance Radar (ARSR) operational comparison

    NASA Astrophysics Data System (ADS)

    Dunbar, Brian; Mittelman, Jeff

    1993-07-01

    The National Weather Service (NWS), Federal Aviation Administration (FAA), and Department of Defense are in the process of fielding the Next Generation Weather Radars (NEXRAD). These doppler weather radars, also known as Weather Surveillance Radar (WSR)-88D, will be replacing the WSR-57 and WSR-74 weather radars in use today. The NEXRAD data will be used by the FAA's Advanced Automation System (AAS) in place of the Air Route Surveillance Radar (ARSR) weather data currently being used by air traffic controllers. Because the NEXRAD's scanning strategy is more time consuming than the ARSR's, there have been some concerns expressed within the FAA about using 'untimely' NEXRAD data in an Air Traffic Control (ATC) environment. In response to these concerns, the FAA's Center for Advanced Aviation System Development (CAASD) at MITRE conducted a study, under the sponsorship of the FAA's National Airspace System (NAS) System Engineering Service (ASE), to assess the relative ability of NEXRAD's and ARSR's to detect and present significant weather in order to determine the operational impact of using NEXRAD data in lieu of ARSR data. The NEXRAD/ARSR operational comparison study is documented.

  8. 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.

  9. 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.

  10. 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.

  11. 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 resolution real-time model simulations possible, the need to obtain observations to both initialize numerical models and verify their output has become increasingly important. The assimilation of high resolution radar observations therefore provides a vital component in the development and utility of numerical model forecasts for both weather forecasting and contaminant transport, including future opportunities to improve wet deposition computations explicitly.

  12. 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.

  13. 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.

  14. 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.

  15. Towards a better representation of radar-rainfall: Filling gaps in understanding uncertainties

    NASA Astrophysics Data System (ADS)

    Seo, Bong Chul

    Radar-rainfall uncertainty quantification has been recognized as an intricate problem due to the complexity of the multi-dimensional error structure, which is also associated with space and time scale. The error structure is usually characterized by two moments of the error distribution: bias and error variance. Despite numerous efforts to investigate radar-rainfall uncertainties, many questions remain unanswered. This dissertation uses two statistical descriptions (mean and variance) of the error distribution to highlight and describe some of the remaining gaps in representing radar-rainfall uncertainties. The four central issues addressed in this dissertation include: 1. Investigation of radar relative bias caused by radar calibration. 2. Statistical modeling of range-dependent error arising from the radar beam geometry structure. 3. Scale-dependent variability of radar-rainfall and rain gauge error covariance. 4. Scale-dependence of radar-rainfall error variance. The first two issues describe systematic features of main error sources of radar-rainfall. The other two are associated with quantifying radar error variance using the error variance separation (EVS) method, which considers the spatial sampling mismatch between radar and rain gauge data. This study captures the main systematic features (systematic bias arising from radar calibration and range-dependent errors) of radar measurements without using ground reference data and the error variance structure with respect to the spatio-temporal transformation of the measurements for further applications to hydrologic fields. Such consideration of radar-rainfall uncertainties represented by error mean and variance can enhance the characterization of the uncertainty structure and yield a better understanding of the physical process of precipitation.

  16. 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

  17. The next generation airborne polarimetric Doppler weather radar

    NASA Astrophysics Data System (ADS)

    Vivekanandan, J.; Lee, W.-C.; Loew, E.; Salazar, J. L.; Grubišić, V.; Moore, J.; Tsai, P.

    2014-07-01

    Results from airborne field deployments emphasized the need to obtain concurrently high temporal and spatial resolution measurements of 3-D winds and microphysics. A phased array radar on an airborne platform using dual-polarization antenna has the potential for retrieving high-resolution, collocated 3-D winds and microphysical measurements. Recently, ground-based phased array radar (PAR) has demonstrated the high time-resolution estimation of accurate Doppler velocity and reflectivity of precipitation and clouds when compared to mechanically scanning radar. PAR uses the electronic scanning (e-scan) to rapidly collect radar measurements. Since an airborne radar has a limited amount of time to collect measurements over a specified sample volume, the e-scan will significantly enhance temporal and spatial resolution of airborne radar observations. At present, airborne weather radars use mechanical scans, and they are not designed for collecting dual-polarization measurements to remotely estimate microphysics. This paper presents a possible configuration of a novel airborne phased array radar (APAR) to be installed on an aircraft for retrieving improved dynamical and microphysical scientific products. The proposed APAR would replace the aging, X-band Electra Doppler radar (ELDORA). The ELDORA X-band radar's penetration into precipitation is limited by attenuation. Since attenuation at C-band is lower than at X-band, the design specification of a C-band airborne phased array radar (APAR) and its measurement accuracies are presented. Preliminary design specifications suggest the proposed APAR will meet or exceed ELDORA's current sensitivity, spatial resolution and Doppler measurement accuracies of ELDORA and it will also acquire dual-polarization measurements.

  18. 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.

  19. 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

  20. Comparison of soft computing systems for the post-calibration of weather radar

    NASA Astrophysics Data System (ADS)

    Hessami Kermani, Masoud Reza

    The most usual tools to monitor rainfall events are raingauges and weather radar. Networks of raingauges provide accurate point estimates of rainfall, when appropriately set, but their usual low density restricts considerably the spatial resolution of the gathered information. Such networks, with rain gauges at distinct points, do not reflect the spatial distribution of rainfall. The quality of raingauge observations is also susceptible to some error sources, for example wind effects around the raingauges and poor raingauge reports due to hardware problems. Radar systems offer high spatial and temporal resolution observation which is much more efficient at providing the space-time evolution of a rainfall event in comparison with raingauge networks. However the radar measurements are not free of errors due to a variety of factors including ground clutter, bright bands, anomalous propagation, beam blockages, and attenuation. The effectiveness of weather radar operation is strongly linked to rigorous calibration. Various methods have been proposed to calibrate radar data. They can be classified into two main categories: deterministic and statistical. The deterministic approach involves the calibration of radar rainfall estimations against raingauge observations. The statistical approach includes multivariate analysis and cokriging. Geostatistical approaches are known as the best methods for radar-raingauge data integration but they are usually inefficient in real time, especially when dealing with the sampling rates of one hour or less necessary for urban and small watershed applications. Such methods also rely on a strong human expertise which can lead to user-dependent results. The objectives of this research are to introduce and to investigate the feasibility of soft computing systems for the post-calibration of weather radar in comparison with the best existing method based on geostatistics. In this work, the soft computing systems include artificial neural networks and Adaptive Neuro-Fuzzy Inference System (ANFIS) and the geostatistical approach includes residual kriging. The residual kriging calibration results are satisfying however this method is based on stationary hypotheses and requires variogram modeling, making it difficult in an operational context. This method has the advantage of providing a mean squared errors map based on variogram modeling for the estimations. For the artificial neural network, thirteen variants of the multilayer feedforward networks and two variants of radial basis functions are tested in this work. The neural calibration results showed that the Levenberg-Marquardt algorithm using Bayesian regularization is robust and reliable for radar-raingauge data integration. The ANFIS offers the precision and learning capability of artificial neural networks combined with the advantages of fuzzy logic. This method based on the Jackknife approach allows the use of all the available data for training and checking the neuro-fuzzy inference system, and provides a degree of reliability of the post-calibration. The training and the interpolation results of proposed methods can be obtained within just a few seconds using an ordinary personal computer, which is incomparably faster than geostatistical approaches. The proposed algorithms would be very efficient for real time post-calibration.

  1. 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 application has been evaluated with reference to its suitability in supporting proper monitoring usage, with emphasis on the readiness of observations, and hydrological modelling, where the robustness of the quantitative estimates is focused.

  2. 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.

  3. 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

  4. 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.

  5. 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 propagated through the model to assess its influence on the forecasted flow uncertainty. Furthermore, the effects of uncertainties at different forecast lead times on potential abstraction strategies are assessed. The results show that over a 10 year period, an average of approximately 70 ML/d of potential water is missed in the study catchment under a convention abstraction regime. This indicates a considerable potential for the use of flow forecasting models to effectively implement advanced abstraction management and more efficiently utilize available water resources in the study catchment.

  6. 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.

  7. 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.

  8. 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.

  9. Doppler weather radar based nowcasting of cyclone Ogni

    NASA Astrophysics Data System (ADS)

    Roy, Soma Sen; Lakshmanan, V.; Roy Bhowmik, S. K.; Thampi, S. B.

    2010-04-01

    In this paper, we describe offline analysis of Indian Doppler Weather Radar (DWR) data from cyclone Ogni using a suite of radar algorithms as implemented on NEXRAD and the advanced algorithms developed jointly by the National Severe Storms Laboratory (NSSL) and the University of Oklahoma. We demonstrate the applicability of the various algorithms to Indian radar data, the improvement in the quality control and evaluate the benefit of nowcasting capabilities in Indian conditions. New information about the tropical cyclone structure, as derived from application of the algorithms is also discussed in this study. Finally, we suggest improvements that could be made to the Indian data collection strategies, networking and real-time analysis. Since this is the first study of its kind to process and utilize DWR data in a tropical climate, the suggestions on real-time analysis and data collection strategies made in this paper, would in many cases, be beneficial to other countries embarking on DWR network modernization programs.

  10. Comparative Analysis of Radar and Gauge Rainfall Data By The A,b-diagrams

    NASA Astrophysics Data System (ADS)

    Pavlyukov, Yu. B.; Melnichuk, Yu. V.

    For hydrology application it's important that radar rainfall measurements correspond to gauge data more precisely as possible. In fact only ground measurements are sole criterion of radar rainfall measurements quality. But this criterion isn't absolute: firstly, gauges as well as radars have some own errors, secondly accurate correspondence of radar and gauges data we can't wait because of principal inequality of instrument sensitive volumes. For correct calibration radar main part of its rainfall measurement inaccuracy determines by natural DSD variations, under condition of exact measure- ment of Z. Obviously that if we know "radar zone-average" DSD characteristics (and its bind bulk parameters, as A and b coefficients in Z-R relations) we can have essen- tial increased accuracy of radar rainfall measurements. This information is interesting for the best understanding of natural parameter variation limits. But we haven't clear understanding about the coefficients variation magnitude for different types of precip- itation as yet. In present report we investigate the behavior of statistical consistency criteria of radar and gauge rainfall data, such as regression coefficient, RMS differ- ence, correlation coefficient, in A,b-parameters space on purpose to find parameter set of optimal radar-to-gauge data accordance. Such analysis has allowed us to reveal interesting features of optimal parameter value distribution in different precipitation conditions. Proposed approach for data analysis is applicable to identification aver- aged parameters for different length rainfall accumulation period: from few minutes to day, decade, season etc. Our conclusions are corroborated by the examples from our long time period radar observations of summer and winter precipitations by dual- bands (S and X) radar in Moscow.

  11. 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 Hydrometeorology 6: 532-549 http://dx.doi.org/10.1175/JHM433.1 Berenguer M, D Sempere, G Pegram, 2011: SBMcast - An ensemble nowcasting technique to assess the uncertainty in rainfall forecasts by Lagrangian extrapolation. Journal of Hydrology 404: 226-240 http://dx.doi.org/10.1016/j.jhydrol.2011.04.033

  12. Where the Least Rainfall Occurs in the Sahara Desert, the TRMM Radar Reveals a Different Pattern of Rainfall Each Season

    NASA Technical Reports Server (NTRS)

    Kelley, Owen A.

    2014-01-01

    Some previous studies were unable to detect seasonal organization to the rainfall in the Sahara Desert, while others reported seasonal patterns only in the less-arid periphery of the Sahara. In contrast, the precipitation radar on the Tropical Rainfall Measuring Mission (TRMM) satellite detects four rainy seasons in the part of the Sahara where the TRMM radar saw the least rainfall during a 15-yr period (1998-2012). According to the TRMM radar, approximately 20 deg-27 deg N, 22 deg-32 deg E is the portion of the Sahara that has the lowest average annual rain accumulation (1-5 mm yr(exp -1)). Winter (January and February) has light rain throughout this region but more rain to the north over the Mediterranean Sea. Spring (April and May) has heavier rain and has lightning observed by the TRMM Lightning Imaging Sensor (LIS). Summer rain and lightning (July and August) occur primarily south of 23 deg N. At a maximum over the Red Sea, autumn rain and lightning (October and November) can be heavy in the northeastern portion of the study area, but these storms are unreliable: that is, the TRMM radar detects such storms in only 6 of the 15 years. These four rainy seasons are each separated by a comparatively drier month in the monthly rainfall climatology. The few rain gauges in this arid region broadly agree with the TRMM radar on the seasonal organization of rainfall. This seasonality is reason to reevaluate the idea that Saharan rainfall is highly irregular and unpredictable.

  13. 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.

  14. 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 precipitation, the surface return over a single 360 degree sweep over -25 h-diameter region provides information on the surface wind speed and direction within the scan circle. In precipitation regions, the conical scan with appropriate mapping and analysis provides the 3D structure of reflectivity beneath the plane and the horizontal winds. The use of conical scanning in hurricanes has recently been demonstrated for measuring inner core winds with the IWRAP system flying on the NOAA P3's. In this presentation, we provide a description of the URAD system hardware, status, and future plans. In addition to URAD, NASA SBIR activity is supporting a Phase I study by Remote Sensing Solutions and the University of Massachusetts for a dual-frequency IWRAP for a high altitude UAV that utilizes solid state transmitters at 14 and 35 GHz, the same frequencies that are planned for the radar on the Global Precipitation System satellite. This will be discussed elsewhere at the meeting.

  15. The impact of reflectivity correction and accounting for raindrop size distribution variability 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

    2014-11-01

    Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z - R) and radar reflectivity-specific attenuation (Z - k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.

  16. 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.

  17. Terminal Doppler weather radar operational test and evaluation, Orlando 1990

    NASA Astrophysics Data System (ADS)

    Bernella, David M.

    1991-04-01

    Lincoln Laboratory conducted an evaluation of the Federal Aviation Administration (FAA) Terminal Doppler Weather Radar (TDWR) system in Orlando, Florida during the summer of 1990. In previous years, evaluations have been conducted at airports in Kansas City, MO (1989) and Denver, CO (1988). Since the testing at the Kansas City International Airport, the radar was modified to operate in C-band, which is the intended frequency band for the production TDWR systems. The objectives of the 1990 evaluation period were to evaluate TDWR system performance in detecting low-altitude wind shear, specifically microbursts and gust fronts, at the Orlando International Airport and in the surrounding area; to refine the system's wind shear detection capabilities; and to evaluate elements of the system developed by the contractor, which were new for the C-band system and therefore not available for evaluation in previous years. Some performance comparisons are made among results from the vastly different weather environments of Denver, Kansas City, and Orlando. Statistics are presented and discussed for the performance of the system in detecting and predicting microbursts and gust fronts. A significant use of the prediction capability is its potential use for air traffic control (ATC) personnel to plan airport operations when hazardous weather is predicted. Issues such as low velocity ground clutter (from tree leaves, road traffic, and dense urban areas) that affect prediction performance are discussed along with possible software modification to account for them.

  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. Superconducting Narrowband Filter for Receiver of Weather Radar

    NASA Astrophysics Data System (ADS)

    Kawaguchi, Tamio; Shiokawa, Noritsugu; Nakayama, Kohei; Watanabe, Takatoshi; Hashimoto, Tatsunori; Kayano, Hiroyuki

    We have developed a high-temperature superconducting (HTS) filter with narrow bandwidth characteristic for receiver of weather radar in order to reduce interference between adjacent radar channels. To realize a filter with which a narrow bandwidth and low insertion loss are compatible, resonators with high unloaded Q (Qu) value are required. Hairpin microstrip resonators with 1.5 times wavelength were adopted to suppress the radiation loss and achieve a high Qu value. The developed HTS filter has 8-pole quasi-elliptic function response for sharp skirt characteristic. The measured frequency response of the developed filter shows center frequency of 5370MHz, insertion loss of 2.04dB and maximum return loss of 15dB, which agrees with the designed responses.

  20. Assimilation of Doppler Weather Radar Data in WRF Model for Simulation of Tropical Cyclone Aila

    NASA Astrophysics Data System (ADS)

    Srivastava, Kuldeep; Bhardwaj, Rashmi

    2014-08-01

    For the accurate and effective forecasting of a cyclone, it is critical to have accurate initial structure of the cyclone in numerical models. In this study, Kolkata Doppler weather radar (DWR) data were assimilated for the numerical simulation of a land-falling Tropical Cyclone Aila (2009) in the Bay of Bengal. To study the impact of radar data on very short-range forecasting of a cyclone's path, intensity and precipitation, both reflectivity and radial velocity were assimilated into the weather research and forecasting (WRF) model through the ARPS data assimilation system (ADAS) and cloud analysis procedure. Numerical experiment results indicated that radar data assimilation significantly improved the simulated structure of Cyclone Aila. Strong influences on hydrometeor structures of the initial vortex and precipitation pattern were observed when radar reflectivity data was assimilated, but a relatively small impact was observed on the wind fields at all height levels. The assimilation of radar wind data significantly improved the prediction of divergence/convergence conditions over the cyclone's inner-core area, as well as its wind field in the low-to-middle troposphere (600-900 hPa), but relatively less impact was observed on analyzed moisture field. Maximum surface wind speed produced from DWR-Vr and DWR-ZVr data assimilation experiments were very close to real-time values. The impact of radar data, after final analysis, on minimum sea level pressure was relatively less because the ADAS system does not adjust for pressure due to the lack of pressure observations, and from not using a 3DVAR balance condition that includes pressure. The greatest impact of radar data on forecasting was realized when both reflectivity and wind data (DWR-ZVr and DWR-ZVr00 experiment) were assimilated. It is concluded that after final analysis, the center of the cyclone was relocated very close to the observed position, and simulated cyclone maintained its intensity for a longer duration. Using this analysis, different stages of the cyclone are better captured, and cyclone structure, intensification, direction of movement, speed and location are significantly improved when both radar reflectivity and wind data are assimilated. As compared to other experiments, the maximum reduction in track error was noticed in the DWR-ZVr and DWR-ZVr00 experiments, and the predicted track in these experiments was very close to the observed track. In the DWR-ZVr and DWR-ZVr00 experiments, rainfall pattern and amount of rainfall forecasts were remarkably improved and were similar to the observation over West Bengal, Orissa and Jharkhand; however, the rainfall over Meghalaya and Bangladesh was missed in all the experiments. The influence of radar data reduces beyond a 12-h forecast, due to the dominance of the flow from large-scale, global forecast system models. This study also demonstrates successful coupling of the data assimilation package ADAS with the WRF model for Indian DWR data.

  1. TDWR (Terminal Doppler Weather Radar) scan strategy requirements

    NASA Astrophysics Data System (ADS)

    Campbell, S. D.; Merritt, M. W.

    1988-11-01

    The requirements for the scan strategy to be employed in the Terminal Doppler Weather Radar (TDWR) are described. The report is divided into three main sections: rationale, example scan strategy and requirements. The rationale for the TDWR scan strategy is presented in terms of: (1) detection of meteorological phenomena, and (2) minimization of range and velocity folding effects. Next, an example is provided based on an experimental scan strategy used in Denver during the summer of 1987. Finally, the requirements for the TDWR scan strategy are presented based on the preceeding discussion. Also, an appendix is included describing the proposed criteria for switching between scan modes.

  2. 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.

  3. 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.

  4. 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.

  5. A Radar Climatology of Extreme Rainfall in the Front Range of the Rocky Mountains

    NASA Astrophysics Data System (ADS)

    Javier, J. R.; Smith, J. A.; England, J. F.; Baeck, M.

    2004-12-01

    Analyses of the spatial and temporal distribution of extreme rainfall in the Arkansas River basin above Pueblo, Colorado are based on analyses of volume scan radar reflectivity observations from the Pueblo and Denver WSR-88D radars for the period 1995 - 2004. Climatological analyses of extreme rainfall are carried out both from an Eulerian perspective, in which the time-varying distribution of rainfall at fixed locations is examined, and a Lagrangian perspective, in which distributional aspects of rainfall are based on storm tracking algorithms. Of particular interest is the spatial heterogeneity of extreme rainfall in the complex terrain of the upper Arkansas River basin. Lagrangian analyses are used to characterize the spatially varying distribution of storm initiation, storm motion and storm structure. Analyses are motivated by problems of dam safety in which distributional properties of extreme rainfall are of most interest. Climatological analyses of extreme rainfall in the upper Arkansas River basin are examined relative to the spatial and temporal properties of two extreme rain events that occurred in June 1921 and June 1964. Radar climatology indicates a lack of spatial coherence in extreme events over the basin, with the upper basin rainfall climatology exhibiting pronounced contrasts with that of the lower basin.

  6. 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.

    2015-04-01

    There are many potential sources of bias in the radar rainfall estimation process. This study classified the biases from the rainfall estimation process into the reflectivity measurement bias and QPE model bias 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). For the Z bias correction, this study utilized the bias correction algorithm for the reflectivity. The concept of this algorithm is that the reflectivity of 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 rainfall-bias. The Z bias and rainfall-bias correction methods were applied to the RAR system. The accuracy of the RAR system improved after correcting Z bias. For rainfall types, although the accuracy of Changma front and local torrential cases was slightly improved without the Z bias correction, especially, the accuracy of typhoon cases got worse than existing results. As a result of the rainfall-bias correction, the accuracy of the RAR system performed 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 rainfall types, Results of the Z bias_LGC showed that rainfall estimates for all types was more accurate than only the Z bias and, especially, outcomes in typhoon cases was vastly superior to the others.

  7. 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 experiments in which these radar-based precipitation estimates and dynamic model-and automated algorithm-based precipitation simulations are used as input to a surface-hydrologic model for simulation of the stream discharge associated with the flood.

  8. 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

  9. 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 for interactive data exploration and analysis. Based on the powerful scientific python stack (numpy, scipy, matplotlib) and in parts augmented by functions compiled in C or Fortran, most routines are fast enough to also allow data intensive re-analyses or even real-time applications. From the organizational point of view, wradlib is intended to be community driven. To this end, the source code is made available using a distributed version control system (DVCS) with a publicly hosted repository. Code may be contributed using the fork/pull-request mechanism available to most modern DVCS. Mailing lists were set up to allow dedicated exchange among users and developers in order to fix problems and discuss new developments. Extensive documentation is a key feature of the library, and is available online at http://wradlib.bitbucket.org. It includes an individual function reference as well as examples, tutorials and recipes, showing how those routines can be combined to create complete processing workflows. This should allow new users to achieve results quickly, even without much prior experience with weather radar data.

  10. Technical Note: An open source library for processing weather radar data (wradlib)

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

    The potential of weather radar observations for hydrological and meteorological research and applications is undisputed, particularly with increasing world-wide radar coverage. However, several barriers impede the use of weather radar data. These barriers are of both scientific and technical nature. The former refers to inherent measurement errors and artefacts, the latter to aspects such as reading specific data formats, geo-referencing, visualisation. The radar processing library wradlib is intended to lower these barriers by providing a free and open source tool for the most important steps in processing weather radar data for hydro-meteorological and hydrological applications. Moreover, the community-based development approach of wradlib allows scientists to share their knowledge about efficient processing algorithms and to make this knowledge available to the weather radar community in a transparent, structured and well-documented way.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Enhancements to the terminal Doppler weather radar gust front algorithm

    NASA Astrophysics Data System (ADS)

    Hermes, Laurie G.; Thomas, Kevin W.; Stumpf, Gregory J.; Eilts, Michael D.; Brandes, Edward; Zrnic, Dusan; Doviak, Richard; Witt, Arthur

    1990-12-01

    During the 1988 Operational Test and Evaluation of the FAA's Terminal Doppler Weather Radar (TDWR) system, a real-time test of the gust front algorithm capabilities in a High Plains environment (Denver, CO) was accomplished. Further evaluation of the algorithm's detection capability in the Great Planes (Kansas City, KA) was conducted in 1989. Deficiencies in several techniques used by the TDWR gust front algorithm were noted. As a result, modifications such as feature error checking and feature checking prior to polynomial fitting were included in the algorithm. Improvements to the techniques used to vertically associate features, determine gust front orientations, and to produce gust front representations and forecasts were also implemented. False algorithm detections, specifically those caused by the detection of radial convergence associated with low-level jet phenomenon, are discussed.

  16. 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 reduces the complexity from "NxN" transmit/receive (T/R) modules of a conventional planar-phased array to just "N" T/R modules. The antenna uses T/R modules with electronic phase-shifters for beam steering. The offset reflector does not provide poor cross-polarization like a double- curved offset reflector would, and it allows the wide scan angle in one plane required by the mission. Also, the cylindrical reflector with two linear array feeds provides dual-frequency performance with a single, shared aperture. The aperture comprises a reflective surface with a focal length of 1.89 m and is made from aluminized Kapton film. The reflective surface is of uniform thickness in the range of a few thousandths of an inch and is attached to the chain-link support structure via an adjustable suspension system. The film aperture rolls up, together with the chain-link structure, for launch and can be deployed in space by the deployment of the chain-link structure.

  17. 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

  18. 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 generation until late winter, even when intense convective storms took place. For this reason, about 86% of all precipitation events produce insignificant recharge contributions. Recharge responses to individual storms were nonlinear and did not cluster well with either storm amount or storm classification type. For example, ~7% of rainfall events fall near the 1:1 rainfall/recharge line and these events represent about 37% of cumulative recharge, and individual storms accounted for up to 4% of their annual totals. However, recharge events in late winter are mainly triggered by stratiform precipitation whereas in spring they are generally generated by convective storms. This novel approach to assessing storm-scale recharge may be relevant to several current challenges in the characterization of groundwater recharge processes, including the evaluation of their spatiotemporal distributions and the impacts of climate change on groundwater.

  19. 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.

  20. 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.

  1. 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.

  2. Weather radar equation and a receiver calibration based on a slice approach

    NASA Astrophysics Data System (ADS)

    Yurchak, B. S.

    2012-12-01

    Two circumstances are essential when exploiting radar measurement of precipitation. The first circumstance is a correct physical-mathematical model linking parameters of a rainfall microstructure with a magnitude of a return signal (the weather radar equation (WRE)). The second is a precise measurement of received power that is fitted by a calibration of radar receiver. WRE for the spatially extended geophysical target (SEGT), such as cloud or rain, has been derived based on "slice" approach [1]. In this approach, the particles located close to the wavefront of the radar illumination are assumed to produce backscatter that is mainly coherent. This approach allows the contribution of the microphysical parameters of the scattering media to the radar cross section to be more comprehensive than the model based on the incoherent approach (e.g., Probert-Jones equation (PJE)). In the particular case, when the particle number fluctuations within slices pertain the Poisson law, the WRE derived is transformed to PJE. When Poisson index (standard deviation / mean number of particles) of a slice deviates from 1, the deviation of return power estimated by PJE from the actual value varies from +8 dB to - 12 dB. In general, the backscatter depends on mean, variance and third moment of the particle size distribution function (PSDF). The incoherent approach assumes only dependence on the sixth moment of PSDF (radar reflectivity Z). Additional difference from the classical estimate can be caused by a correlation between slice field reflectivity [2]. Overall, the deviation in particle statistics of a slice from the Poisson law is one of main physical factors that contribute to errors in radar precipitation measurements based on Z-conception. One of the components of calibration error is caused by difference between processing by weather radar receiver of the calibration pulse, and actual return signal from SEGT. A receiver with non uniform amplitude-frequency response (AFR) processes these signals with the same input power but with different radio-frequency spectrums (RFS). This causes different output magnitude due to different distortion experienced while RFS passing through a receiver filter. To assess the calibration error, RFS of signals from SEGT has been studied including theoretical, experimental and simulation stages [3]. It is shown that the return signal carrier wave is phase modulated due to overlapping of replicas of RF-probing pulse reflected from SEGT's slices. The RFSs depends on the phase statistics of the carrier wave and on RFS of the probing pulse. The bandwidth of SEGT's RFS is not greater than that of the probing pulse. Typical phase correlation interval was found to be around the same as that of the probing pulse duration. Application of a long calibration signal (proportional to SEGT extension) causes the error up to -1 dB for conventional radar with matched filter. To eliminate the calibration error, a power estimate of individual return waveform should be corrected with the transformation loss coefficient calculated based on RFS and AFR parameters. To embrace with calibration the high and low frequency parts of a receiver, the calibration should be performed with a long pulse. That long pulse is composed from adjoining replicas of a probe pulse with random initial phases and having the same magnitude governed by the power of probe pulse.

  3. 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 network during heavy rain and rain/hail mixture events. The X-band radar measurements also were generally successful in capturing the high spatial variability in convective rainfall, which caused post-fire debris flows.

  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. 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.

  6. 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.

  7. 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 not yield the same parameters in terms of spatial distribution and temporal evolution. CALAMAR product seems to significantly under-estimates rainfall singularities and yields a higher percentage of zero values. This may results from the fact CALAMAR replaces the ground clutters by zero values. Authors acknowledge the European INTERREG IV NEW RainGain project (http://raingain.eu) for partial financial support.

  8. The space-time structure of radar rainfall in complex terrain

    NASA Astrophysics Data System (ADS)

    Savina, M.; Molnar, P.; Burlando, P.

    2009-04-01

    The space-time structure in rainfall fields is affected by topography to the extent that topography influences the multitude of processes that lead to precipitation on the ground, e.g., orographic forcing of moist air flow, condensation, convective activity, wind speeds and directions, etc. One way to analyse the structure in space-time precipitation fields is to study the time evolution of cumulated rainfall fields from radar data. Rainfall organization leads to a scaling relationship between the spatial variance and time with a characteristic scaling exponent H which is indicative of the nature of the memory (short or long) in the data. Rodriguez-Iturbe et al. (1998) developed this technique to show that space-time rainfall from radar at a daily time resolution exhibited consistent scaling and long-term memory (H>0.5) over a rather flat area of the Arkansas-Red River Basin in the U.S. In this paper we investigate whether the time evolution of cumulated rainfall fields from radar data may be used in topographically complex terrain to study if topography has a measurable effect on the space-time structure of rainfall and to quantify this effect. We apply the method of Rodriguez-Iturbe et al. (1998) to determine the scaling relationship and characteristic scaling exponent H between the spatial variance and mean of rainfall measured by radar on a 120x120 km domain centered on the main Alpine divide around Kl. Matterhorn, covering parts of Switzerland and Italy. The radar product we use is the 30-min precipitation depth estimated at the ground at a 1 km grid resolution from MeteoSwiss C-band radar for a continuous period of about one year. The altitude within the study domain ranges from 140 to 4520 m. As a first step the exponent H was evaluated by subdividing the study domain into 5x5 sub-domains, each with a resolution of 24x24 km, and averaging. We found that the scaling relationship is consistent and that long-term memory is present (H=0.84). We then evaluated H separately for each realization in each sub-domain and correlated it with topographic attributes of the sub-domain, such as mean altitude, relief, dominant aspect, etc. We found that H was statistically significantly correlated with mean altitude, with higher H present at higher altitudes where local topographic features lead to singularities in the rainfall field which increase the variance. However, at the same time the total rainfall amount was not well correlated with altitude, which suggests that it is the organization of the space-time structure in rainfall, not simply rainfall amount that is affected by topography. This study contributes observational evidence to the effect of orography on rainfall and the utility of radar data to study the space-time structure of rainfall.

  9. Evaluating the Potential of Radar-based Rainfall Estimates for Stream Flow Simulation in the Philippines

    NASA Astrophysics Data System (ADS)

    Abon, C. C.; Kneis, D.; Bronstert, A.; Crisologo, I.; David, C. P. C.; Heistermann, M.

    2014-12-01

    This study evaluates the suitability of radar-based quantitative precipitation estimates (QPE) for the simulation of stream flow in the Marikina River Basin (535 km2), The Philippines. We used observed reflectivity from the wet season period of 2012 and 2013 from an S-band radar near Subic. Radar data processing and precipitation estimation were carried out using the Open Source library wradlib. To evaluate the potential added value of radar-based QPE, we generated a benchmark precipitation product based on the interpolation of rain gauge observations (GO product). The GO product was also used to quantify rainfall estimation errors at the point scale. For stream flow simulation, we used a semi-distributed conceptual hydrological model based on the Open Source ECHSE framework. At the point scale, the radar-based QPE was benchmarked against the GO product at daily and hourly accumulation intervals. It turned out that the radar-based QPE outperformed the GO product in the 2012 while the performance was similar in the 2013. For both periods, estimation errors substantially increased from the daily to the hourly accumulation intervals, most likely due to a lack of representativeness at the point scale. Interestingly, though, the hourly rainfall estimates allowed for a good simulation of observed stream flow when used to force the hydrological model. In particular, the two main flood events, induced by an enhanced South-West monsoon, are well represented using both hourly rainfall products. The results show that the quality of the simulated stream flow was well in line with the point-based verification: while the radar-based QPE clearly outperforms the GO product in 2012, both perform similarly in 2013. The hydrological model had been recalibrated for each rainfall product to allow for a fair comparison of the two competing rainfall products. As the Marikina River Basin has a comparatively dense rain gauge network, the results of this study are encouraging with respect to usability of the radar-based QPE in other parts of the Philippines where dense rain gauge network are not available.

  10. Ground-based weather radar compatibility with digital radio-relay microwave systems

    NASA Astrophysics Data System (ADS)

    Gawthrop, P. E.; Patrick, G. M.

    1990-03-01

    The potential for ground-based weather radar (meteorological radar) interference to digital microwave systems in the common carrier bands of 3700 to 4200 MHz and 5925 to 6425 MHz is examined. Reported cases of interference to microwave common carrier systems from ground-based weather radar systems have increased due to the trend towards digital modulations. Because of this interference, the National Telecommunications and Information Administration, the Federal Communications Commission and the National Spectrum Managers Association formed an informal working group to investigate and document the potential problems. The existing and planned spectrum uses by ground-based weather radars and digital microwave systems are addressed as well as regulations and policy pertaining to their electromagnetic compatibility. Methods to mitigate the interference in both the radar transmitter and microwave receiver are also provided.

  11. High-resolution rainfall signatures on X-band Synthetic Aperture Radar imagery: model analysis and experimental validation

    NASA Astrophysics Data System (ADS)

    Marzano, F. S.; Mori, S.; Mugnai, A.; Weinman, J. A.

    2009-04-01

    Climate modelers need global precipitation measurements because the released latent heat distribution has a profound effect on the performance of such models. Precipitation measurements are also required to facilitate water management strategies by hydrologists, and managers of transportation, agricultural and flood relief agencies. Although precipitation measurements are widely available in technologically advanced countries, the measurement of precipitation over oceans, mountainous terrain and less developed regions leaves much to be desired. Since the 1980s much of our understanding of global precipitation has been provided by space-borne passive microwave radiometers and a combination of microwave and infrared passive measurements. Unfortunately space-borne microwave radiometers, even in combination with infrared sensors, have had limited success in retrieving precipitation over land because they rely heavily on the scattering properties of ice in the upper regions of precipitating clouds. Those scattering properties may be poorly related to surface rainfall rates. This limitation can be overcome over land by space-based radars operating at X or Ku band. The Ku band Precipitation Radar (PR) aboard the Tropical Rainfall Measurement Mission (TRMM) program has provided unique precipitation measurements over land. Mountainous terrain has presented challenges to both ground and space-based radars. Radar reflectivity measurements from PR are routinely removed within about 1 to 2 kilometers from mountainous surfaces to avoid ground clutter. If significant shallow precipitation or rain cells smaller than the 4 km horizontal resolution occur along mountain slopes, then such precipitation may be missed by PR. The measurement of light, small rain cells may also be impaired by the signal-to-noise ratio floor of the PR. A new opportunity to measure precipitation from space may be afforded by the forthcoming availability of several X-band Synthetic Aperture Radars (X-SARs). The TerraSAR-X (TSX) was launched on June 15, 2007 by the Deutsches Zentrum f. Luft u. Raumfahrt (DLR) and another X-SAR will be launched by 2009. The Constellation of Small Satellites for Mediterranean basin Observations (COSMO-SkyMed, CSK) will be launched by the Agenzia Spaziale Italiana (ASI) within 2009. The first of four of these satellites was launched by ASI on June 7, 2007. The Israeli Defense Ministry plans to launch yet another X-band SAR, the TecSAR SAR Technology Demonstration Satellite, later in 2009. Space-borne X-SARs are generally not designed for atmospheric observation. SARs are often considered "all weather" sensors. However, there is relevant theoretical and experimental evidence that X-band radar may be significantly affected by precipitation occurrence within the synthetically scanned area [9]-[13]. As a matter of fact, PR was designed at Ku band which is only 4 GHz away from X band. Several authors showed that X-SARs are more sensitive to rainfall effects than SARs operating at longer wavelengths, such as L and C bands [10]-[13]. For example, this was demonstrated by the Shuttle Missions STS-59 and 68 of 1994 and the STS-99 Shuttle Radar Topography Mission (SRTM) of 2000 carrying the first X-SAR along with L and C band SARs. Rainfall reflectivity at X-band may be enhanced by about 12 dB and the attenuation increased by about 4 dB when compared to C-band reflectivity and attenuation. The potential of X-SAR for precipitation retrieval is intriguing. They will probably be able to measure rainfall over land with greater sensitivity than from radiometers. The high spatial resolution (less than 100 m) of X-SARs can provide new insights into the structure of precipitating clouds with respect to PR and its future upgrades. X-SAR platforms could also significantly enhance the planned constellation of satellites carrying microwave radiometers and radars that will be part of the foreseen Global Precipitation Measurements (GPM) mission. These X-SAR satellites, then, may make a valuable contribution to our understanding of the hydrological cycle. This work is devoted to the exploration of the potential of space-borne microwave SAR to estimate rainfall over land from both a model and inversion point of view. The main objective is to provide a framework for a physically-based inversion of SARs measurements at X band over land. The X-SARs potentials for rainfall retrievals will be investigated to design quantitative inversion algorithms. We will concentrate on SAR inversion over land in order to avoid the ambiguities of X-SAR response over ocean in the presence of rainfall. A forward model of SAR response will be illustrated not only the X band, but also at Ku and Ka band where some SAR technology is already available. The inversion methodologies will be extensively illustrated and quantitative applications to X-SAR data will be discussed, dealing with several case studies gathered during overpasses of TerraSAR-X over America and Europe. The latter will be also discussed in terms of rain-field validation using available ground-based weather radar data.

  12. 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.

  13. System Concepts for the Advanced Post-TRMM Rainfall Profiling Radars

    NASA Technical Reports Server (NTRS)

    Im, Eastwood; Smith, Eric A.

    2000-01-01

    Global rainfall is the primary distributor of latent heat through atmospheric circulation. The recently launched Tropical Rainfall Measuring Mission satellite is dedicated to advance our understanding of tropical precipitation patterns and their implications on global climate and its change. The Precipitation Radar (PR) aboard the satellite is the first radar ever flown in space and has provided. exciting, new data on the 3-D rain structures for a variety of scientific uses. However, due to the limited mission lifetime and the dynamical nature of precipitation, the TRMM PR data acquired cannot address all the issues associated with precipitation, its related processes, and the long-term climate variability. In fact, a number of new post-TRMM mission concepts have emerged in response to the recent NASA's request for new ideas on Earth science missions at the post 2002 era. This paper will discuss the system concepts for two advanced, spaceborne rainfall profiling radars. In the first portion of this paper, we will present a system concept for a second-generation spaceborne precipitation radar for operations at the Low Earth Orbit (LEO). The key PR-2 electronics system will possess the following capabilities: (1) A 13.6/35 GHz dual frequency radar electronics that has Doppler and dual-polarization capabilities. (2) A large but light weight, dual-frequency, wide-swath scanning, deployable antenna. (3) Digital chirp generation and the corresponding on-board pulse compression scheme. This will allow a significant improvement on rain signal detection without using the traditional, high-peak-power transmitters and without sacrificing the range resolution. (4) Radar electronics and algorithm to adaptively scan the antenna so that more time can be spent to observe rain rather than clear air. and (5) Built-in flexibility on the radar parameters and timing control such that the same radar can be used by different future rain missions. This will help to reduce the overall instrument development costs. In the second portion of this paper, we will present a system concept for a geostationary rainfall monitoring radar for operations at the geosynchronous Earth Orbit (GEO). In particular, the science requirements, the observational strategy, the instrument design, and the required technologies will be discussed.

  14. 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.

  15. 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.

  16. 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.

  17. Modeling COSMO-SkyMed measurements of precipitating clouds over the sea using simultaneous weather radar observations

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

    Several satellite missions employing X-band synthetic aperture radar (SAR) have been activated to provide high-resolution images of normalized radar cross-sections (NRCS) on land and ocean for numerous applications. Rainfall and wind affect the sea surface roughness and consequently the NRCS from the combined effects of corrugation due to impinging raindrops and surface wind. X-band frequencies are sensitive to precipitation: intense convective cells result in irregularly bright and dark patches in SAR images, masking changes in surface NRCS. Several works have modeled SAR images of intense precipitation over land; less adequately investigated is the precipitation effect over the sea surface. These images are analyzed in this study by modeling both the scattering and attenuation of radiation by hydrometeors in the rain cells and the NRCS surface changes using weather radar precipitation estimates as input. The reconstruction of X-band SAR returns in precipitating clouds is obtained by the joint utilization of volume reflectivity and attenuation, the latter estimated by coupling ground-based radar measurements and an electromagnetic model to predict the sea surface NRCS. Radar signatures of rain cells were investigated using X-band SAR images collected from the COSMO-SkyMed constellation of the Italian Space Agency. Two case studies were analyzed. The first occurred over the sea off the coast of Louisiana (USA) in summer 2010 with COSMO-SkyMed (CSK®) ScanSar mode monitoring of the Deepwater Horizon oil spill. Simultaneously, the NEXRAD S-band Doppler radar (KLIX) located in New Orleans was scanning the same portion of ocean. The second case study occurred in Liguria (Italy) on November 4, 2011, during an extraordinary flood event. The same events were observed by the Bric della Croce C-band dual polarization radar located close to Turin (Italy). The polarimetric capability of the ground radars utilized allows discrimination of the composition of the precipitation volume, in particular distinguishing ice from rain. Results shows that for space-borne SAR at X-band, effects due to precipitation on water surfaces can be modeled using coincident ground-based weather radar measurements.

  18. 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 temporal interpolation + merging methodology are particularly evident in storm events with strong and fast-changing (convective-like) rain cells.

  19. 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.

  20. A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

    NASA Astrophysics Data System (ADS)

    Norin, L.

    2015-02-01

    In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.

  1. A quantitative analysis of the impact of wind turbines on operational Doppler weather radar data

    NASA Astrophysics Data System (ADS)

    Norin, L.

    2014-08-01

    In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in radar line-of-sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind- and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on six years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. We show that this is partly explained by changes in the atmospheric refractive index, bending the radar beams closer to the ground. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. We show that when weather echoes give rise to higher reflectivity values than that of the wind farm, the negative impact of the wind turbines disappears for all spectral moments.

  2. 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.

  3. 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

  4. 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

  5. Singularity-sensitive gauge-based radar rainfall adjustment methods for urban hydrological applications

    NASA Astrophysics Data System (ADS)

    Wang, L.-P.; Ochoa-Rodríguez, S.; Onof, C.; Willems, P.

    2015-09-01

    Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system's dynamics, particularly of peak runoff flows.

  6. 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.

  7. A study of the propagation of rainfall uncertainty in flow forecasting using radar QPF ensembles

    NASA Astrophysics Data System (ADS)

    Berenguer, Marc; Sempere-Torres, Daniel

    2010-05-01

    Radar-based rainfall observations and nowcasts have been successfully used for flow forecasting in small- and medium-sized basins when coupled with distributed rainfall-runoff models. However these quantitative precipitation estimates and forecasts (QPE and QPF) are affected by a number of errors that introduce uncertainty in flow simulations. Recent efforts in the description of the structure of the errors affecting radar QPE and QPF allow us to statistically simulate a number of realizations of these errors respecting their structure in space and time. The analysis carried out here consisted in a Montecarlo experiment of coupling these ensembles of equiprobable rainfall scenarios with the distributed rainfall-runoff model DiCHiTop simulating real-time conditions. The study has been carried out in the Besòs basin (~1000 km2), located in the vicinity of Barcelona (NE Spain). This is a typical Mediterranean basin, highly urbanized, with steep slopes and in which floods occur specially in autumn when convective storms hit the basin. The purpose of this work is twofold: (i) analyzing and quantifying the uncertainty the uncertainty in the resulting flow forecasts, and (ii) studying how the uncertainty in flow forecasts depends on the meteorological situation.

  8. Estimation problems in rainfall modeling

    NASA Astrophysics Data System (ADS)

    Krajewski, Witold F.; Georgakakos, Konstantine P.

    A special session entitled Estimation Problems in Rainfall Modeling was held during the 1985 AGU Fall Meeting in San Francisco, Calif. The session was chaired by Witold F. Krajewski of the Hydrologic Research Laboratory of the National Weather Service (NWS), Silver Spring, Md. The purpose of the session was to bring together researchers interested in a wide range of rainfall-related estimation problems, such as parameter estimation, state estimation, multiple sensor rainfall analysis, and estimation problems in rainfall simulation. The topics of papers presented at the session included parameter estimation of point process models, errors in radar rainfall observations, and sampling aspects of space-state representation of rainfall.

  9. The scattering simulation of DSDs and the polarimetric radar rainfall algorithms at C-band frequency

    NASA Astrophysics Data System (ADS)

    Islam, Tanvir

    2014-11-01

    This study explores polarimetric radar rainfall algorithms at C-band frequency using a total of 162,415 1-min raindrop spectra from an extensive disdrometer dataset. Five different raindrop shape models have been tested to simulate polarimetric radar variables-the reflectivity factor (Z), differential reflectivity (Zdr) and specific differential phase (Kdp), through the T-matrix microwave scattering approach. The polarimetric radar rainfall algorithms are developed in the form of R(Z), R(Kdp), R(Z, Zdr) and R(Zdr, Kdp) combinations. Based on the best fitted raindrop spectra models rain rate retrieval information using disdrometer derived rain rate as a reference, the algorithms are further explored in view of stratiform and convective rain regimes. Finally, an “artificial” algorithm is proposed which considers the developed algorithms for stratiform and convective regimes and uses R(Z), R(Kdp) and R(Z, Zdr) in different scenarios. The artificial algorithm is applied to and evaluated by the Thurnham C-band dual polarized radar data in 6 storm cases perceiving the rationalization in terms of rainfall retrieval accuracy as compared to the operational Marshall-Palmer algorithm (Z=200R1.6). A dense network of 73 tipping bucket rain gauges is employed for the evaluation, and the result demonstrates that the artificial algorithm outperforms the Marshall-Palmer algorithm showing R2=0.84 and MAE=0.82 mm as opposed to R2=0.79 and MAE=0.86 mm respectively.

  10. 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.

  11. Effects of Uncertainty in TRMM Precipitation Radar Path Integrated Attenuation on Interannual Variations of Tropical Oceanic Rainfall

    NASA Technical Reports Server (NTRS)

    Robertson, Franklin R.; Fitzjarrald, Dan E.; Kummerow, Christian D.

    2003-01-01

    Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30 deg N/S) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Time series of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) over the tropical oceans show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. We show that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series. Our analysis of discrepancies between the PR rainfall and attenuation suggests that uncertainty in the assumed drop size distribution and associated attenuation/reflectivity/rainfall relationships inherent in single-frequency radar methods is a serious issue for studies of interannual variability.

  12. 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, stratiform and undefined). These are then used to obtain coherent parameter sets for the radar reflectivity-rainfall rate (Z-R) and radar reflectivity-attenuation (Z-k) relationship, specifically applicable for this event. By applying a single parameter set to correct for both sources of errors, the quality of the rainfall product improves further, leading to >80% of the observed accumulations. However, by differentiating between precipitation type no better results are obtained as when using the operational relationships. This leads to the question: how representative are local disdrometer observations to correct large scale weather radar measurements? In order to tackle this question a Monte Carlo approach was used to generate >10000 sets of the normalized dropsize distribution parameters and to assess their impact on the estimated precipitation amounts. Results show that a large number of parameter sets result in improved precipitation estimated by the weather radar closely resembling observations. However, these optimal sets vary considerably as compared to those obtained from the local disdrometer measurements.

  13. Correcting temporal sampling error in radar-rainfall: Effect of advection parameters and rain storm characteristics on the correction accuracy

    NASA Astrophysics Data System (ADS)

    Seo, Bong-Chul; Krajewski, Witold F.

    2015-12-01

    This study offers a method to correct for the radar temporal sampling error when determining radar-rainfall accumulations. The authors evaluate the correction effect with respect to multiple factors associated with storm advection, rainfall characteristics, and different rainfall accumulation time scales. The advection method presented in this study uses linear interpolation of static rain storm locations observed at two intermittent radar sampling times to correct for the missed rainfall accumulations. The advection correction is applied to the high space (0.5 km) and time (5-min) resolution radar-rainfall products provided by the Iowa Flood Center. We use the ground reference data from a high quality and high density rain gauge network distributed over the Turkey River basin in Iowa to evaluate the advection corrected rain fields. We base our evaluation on six rain events and examine the correction performance/improvement with respect to the advection discretization, spatial grid aggregation, rainfall basin coverage, and conditional average rainfall intensity. The results show that the 1-min advection discretization is sufficient to represent the observed distribution of storm velocities for the presented cases. Grid aggregation that is motivated by the need to expedite the computation may induce errors in estimating advection vectors. The authors found that while the advection correction tends to enhance the QPE accuracy for intense rain storms over small or isolated areas, it has little impact on the improvement of light rain estimation.

  14. 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 get much worse as a result of more frequent, shorter, but more intense rainfall events.

  15. Ground clutter effects in an X-Band Solid State FM-CW weather radar

    NASA Astrophysics Data System (ADS)

    Ligthart, L. P.; Nieuwkerk, L. R.

    A new X-Band Solid State FM-CW weather radar, developed at the Delft University, has been operational since 1989. Attention is given to ground clutter effects in the near range of this radar up to 15 km radar range. Two different types of cluttermaps are used for overall and detailed analysis of ground echoes in absence of rain. Clutter suppression techniques are elucidated. Improvement factors for weather/ground clutter ratios have to be interpreted with care in cases where coherent subtraction techniques are involved, since weather echoes in some areas can be nearly as much correlated as ground targets. Most of the cluttermap data handling and clutter suppression is done in real time by using general purpose computing equipment.

  16. 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.

  17. Efficient method for detecting and tracking rainfall clouds in non-Doppler radar images

    NASA Astrophysics Data System (ADS)

    Raaf, Ouarda; El Hamid Adane, Abd

    2014-01-01

    The precipitation echoes collected by non-Doppler meteorological radar are identified and tracked in the covered area. For that a sequence of images, recorded every 5 min by S-band radar in Bordeaux and previously filtered to remove the ground clutter, is considered. In these images, the radar echoes are labeled as precipitation cells and processed using the method of sum and difference histograms of gray levels. Textural parameters are extracted from these images by slicing an analysis window of 55 pixels. Energy and homogeneity are found to be the best discriminating parameters because each of them clearly assigns the radar echoes to either stratiform or cumuliform clouds. The convective cells mainly differ from the stratiform ones by their texture and the high values of their reflectivity factor. To account for the downpour development, the time variations of barycenter, surface area, and reflectivity factor have been analyzed for the precipitation cells in the sequence of radar images under consideration. In the case of cumuliform cells having reflectivity factor higher than 40 dBZ, the expansion of their surface area and their progress in the observed region constitute important information about the clouds leading to weather extremes.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Probabilistic forecasting of shallow, rainfall-triggered landslides using real-time numerical weather predictions

    NASA Astrophysics Data System (ADS)

    Schmidt, J.; Turek, G.; Clark, M. P.; Uddstrom, M.; Dymond, J. R.

    2008-04-01

    A project established at the National Institute of Water and Atmospheric Research (NIWA) in New Zealand is aimed at developing a prototype of a real-time landslide forecasting system. The objective is to predict temporal changes in landslide probability for shallow, rainfall-triggered landslides, based on quantitative weather forecasts from numerical weather prediction models. Global weather forecasts from the United Kingdom Met Office (MO) Numerical Weather Prediction model (NWP) are coupled with a regional data assimilating NWP model (New Zealand Limited Area Model, NZLAM) to forecast atmospheric variables such as precipitation and temperature up to 48 h ahead for all of New Zealand. The weather forecasts are fed into a hydrologic model to predict development of soil moisture and groundwater levels. The forecasted catchment-scale patterns in soil moisture and soil saturation are then downscaled using topographic indices to predict soil moisture status at the local scale, and an infinite slope stability model is applied to determine the triggering soil water threshold at a local scale. The model uses uncertainty of soil parameters to produce probabilistic forecasts of spatio-temporal landslide occurrence 48~h ahead. The system was evaluated for a damaging landslide event in New Zealand. Comparison with landslide densities estimated from satellite imagery resulted in hit rates of 70-90%.

  4. 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.

  5. 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 rate of recovery of fresh meteorite falls can increase by as much as 3.6x the current rate. The authors' experience to date indicates that the most effective course of action would be to have local meteorite research groups (outside of the US) form research consortia and develop a working relationship with their nation's weather bureau for access to data. These research consortia could utilize the same, proven methods used for US NEXRAD imagery, internet eyewitness report aggregation, seismometry analysis, etc. to locate meteorite falls. The consortia could then recover and analyze meteorite falls and enrich their own research efforts. It would be beneficial to conduct a global program to coordinate the development of methods and data tools, as well as to coordinate meteorite sample sharing and research. Perhaps an institution such as the Meteoritical Society could lead such an effort.

  6. 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.

  7. TDWR (Terminal Doppler Weather Radar) PRF (Pulse Repetition Frequency) selection criteria

    NASA Astrophysics Data System (ADS)

    Crocker, S. C.

    1988-03-01

    The Terminal Doppler Weather Radar (TDWR) system shall provide high quality Doppler radar data on weather phenomena near high traffic airports. These data shall be used in real time by automated TDWR algorithms to detect weather situations which may be hazardous to the safe operation of aircraft within the vicinity of the airport. One of the major factors which could cause the degradation of the quality of these TDWR data is obscuration by distant storm cells. This obscuration is caused by storms located beyond the range interval being sampled by the radar, yet whose radar echo ambiguously folds within the range interval of interest. These range aliased echoes could trigger false detections by the algorithms, and/or cause actual hazardous situations near the airport to remain undetected. By carefully selecting the pulse repetition frequency (PRF) of the radar, range obscuration from distant storms can be minimized over specified airport regions. This document describes techniques for predicting the obscuration as a function of PRF, and details the criteria which shall be used by the TDWR system to automatically and adaptively select an optimal PRF in order to minimize these obscuration effects.

  8. 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.

  9. 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 developed for 6X (6 events per year), 4X, 3X, 2X, 1, 2, 5 and 10 year recurrence, and durations from 5 minutes to 7-days. A comparison is made between DARF derived in these analyses with NOAA Atlas 12 DARF, the USACE Sierra Madre Storm and other DARF developed for the interior Southwest. Orographic increases in DDF are related to the Los Angeles County Flood Control District Hydrology Manual 24-hr 50-yr Precipitation maps, elevation from USGS topographic maps and Mean Annual Precipitation maps.

  10. 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 ultimate goal. The Precipitation Radar (PR) aboard the TRMM satellite is the first ever spaceborne radar dedicated to three-dimensional, global precipitation measurements over the tropics and the subtropics, as well as the detailed synopsis of a wide range of tropical rain storm systems. In only twelve months since launch, the PR, together with other science instruments abroad the satellite have already provided unprecedented insights into the rainfall systems. It is anticipated the a lot more exciting and important rain observations would be made by TRMM throughout its mission duration. While TRMM has provided invaluable data to the user community, it is only the first step towards advancing our knowledge on rain processes and its contributions to climate variability. It is envisioned that a TRMM follow-on mission is needed in such a way to capitalize on the pioneering information provided by TRMM, and its instrument capability must be extended beyond TRMM in such a way to fully address the key science questions from microphysical to climatic time scale. In fact, a number of new and innovative mission concepts have recently put forth for this purpose. Almost all of these new concepts have suggested the utility of a more advanced, high-resolution, Doppler-enabled, vertical profiling radar that can provide multi-parameter observations of precipitation. In this paper, a system concept for a second- gene ration precipitation radar (PR-2) which addresses the above requirements will be described.

  11. 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.

  12. The Terminal Doppler Weather Radar (TDWR) Moving Target Simulator (MTS) at Orlando, Florida

    NASA Astrophysics Data System (ADS)

    Drury, W. H.; Frankovich, J. M.

    1992-08-01

    Monitoring the performance of Doppler weather radars presents special problems since target returns cannot be verified by reference to other systems (e,g., as ASR-9 aircraft reports can be compared with beacon replies). The Terminal Doppler Weather Radar (TDWR) system includes a Moving Target Simulator (MTS) which provides a point target equivalent to a 50 dBZ reflectivity weather return with an apparent radial velocity of 5 m/s. This report describes the installation results for a prototype MTS using the TDWR testbed radar in Orlando, FL. Procedures were developed for improved aiming of the MTS, using aiming of the MTS, using azimuth and elevation adjustments, which are recommended to be incorporated in the production MTS installation procedure. Initial data analyses indicate that the MTS returns from a typical radio tower would be useful for integrity monitoring in fair weather using typical TDWR filters. The use of the MTS when high -reflectivity weather or anomalous propagation (AP) is present needs further study.

  13. 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.

  14. 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.

  15. Rainfall and Snowfall Observations by the Airborne Dual-frequency Precipitation Radar during the Wakasa Bay Experiment

    NASA Technical Reports Server (NTRS)

    Tanelli, Simone; Im, Eastwood; Durden, Stephen L.; Meagher, Jonathan P.

    2004-01-01

    Radar data obtained through the NASA/JPL Airborne Precipitation Radar APR-2 during the Wakasa Bay Experiment in January/February 2003 were processed to obtain calibrated reflectivity measurements, rainfall/snowfall velocity measurements, classification of the surface type and detection of the boundaries of the melting layer of precipitation. In this paper the processing approach is described together with an overview of the resulting data quality and known issues.

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

    NASA Astrophysics Data System (ADS)

    Borga, M.; Creutin, J. D.

    Flood risk mitigation is accomplished through managing either or both the hazard and vulnerability. Flood hazard may be reduced through structural measures which alter the frequency of flood levels in the area. The vulnerability of a community to flood loss can be mitigated through changing or regulating land use and through flood warning and effective emergency response. When dealing with flash-flood hazard, it is gener- ally accepted that the most effective way (and in many instances the only affordable in a sustainable perspective) to mitigate the risk is by reducing the vulnerability of the involved communities, in particular by implementing flood warning systems and community self-help programs. However, both the inherent characteristics of the at- mospheric and hydrologic processes involved in flash-flooding and the changing soci- etal needs provide a tremendous challenge to traditional flood forecasting and warning concepts. In fact, the targets of these systems are traditionally localised like urbanised sectors or hydraulic structures. Given the small spatial scale that characterises flash floods and the development of dispersed urbanisation, transportation, green tourism and water sports, human lives and property are exposed to flash flood risk in a scat- tered manner. This must be taken into consideration in flash flood warning strategies and the investigated region should be considered as a whole and every section of the drainage network as a potential target for hydrological warnings. Radar technology offers the potential to provide information describing rain intensities almost contin- uously in time and space. Recent research results indicate that coupling radar infor- mation to distributed hydrologic modelling can provide hydrologic forecasts at all potentially flooded points of a region. Nevertheless, very few flood warning services use radar data more than on a qualitative basis. After a short review of current under- standing in this area, two 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.

  17. 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.

  18. 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.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Evans, James E.

    1988-06-01

    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.

  1. 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 decreases from 1181 to 171 mm a-1 (application period: 2005, 2006 and 2009) and from 317 to 178 mm a-1 (validation period: 2007, 2008). The entire correction scheme is applicable on an annual scale. The correction of mean annual rain amounts derived from radar composite data for the whole period leads to an almost undisturbed and homogeneous distribution of rain amounts for Germany.

  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 Marikina River, the local officials used this information and determined that the river would overflow in a few hours. It gave them a critical lead time to evacuate residents along the floodplain and no casualties were reported after the event.

  3. 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.

  4. 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 considered as constant, in case of rain, at X-SAR incidence angles, it exhibits a dependence to precipitation event due the combined effects of corrugation due to the impinging raindrops and to the surface wind. Therefore, when retrieving of X-SAR NRCS in precipitation over the sea, this effect must be accounted for and can be quantified based on the precipitation event using a simple NRCS surface model. In this work, an EM model based on Bahar's Full Wave Model is used for evaluating such NRCS depending on polarization, frequency and incidence angle for different values of wind velocity and the root mean square height of the corrugation induced by rainfall. The reconstruction of X-SAR returns in precipitation is finally obtained by joint utilization of volume reflectivity and attenuation estimated from KLIX and the sea NRCS model.

  5. Performance of high-resolution X-band weather radar networks - the PATTERN example

    NASA Astrophysics Data System (ADS)

    Lengfeld, K.; Clemens, M.; Münster, H.; Ament, F.

    2014-12-01

    This publication intends to prove that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) project observing precipitation with a temporal resolution of 30 s, a range resolution of 60 m and a sampling resolution of 1° in the azimuthal direction. The network covers an area of 60 km × 80 km. In this paper, algorithms used to obtain undisturbed precipitation fields from raw reflectivity data are described, and their performance is analysed. In order to correct operationally for background noise in reflectivity measurements, noise level estimates from the measured reflectivity field are combined with noise levels from the last 10 time steps. For detection of non-meteorological echoes, two different kinds of clutter algorithms are applied: single-radar algorithms and network-based algorithms. Besides well-established algorithms based on the texture of the logarithmic reflectivity field (TDBZ) or sign changes in the reflectivity gradient (SPIN), the advantage of the unique features of the high temporal and spatial resolution of the network is used for clutter detection. Overall, the network-based clutter algorithm works best with a detection rate of up to 70%, followed by the classic TDBZ filter using the texture of the logarithmic reflectivity field. A comparison of a reflectivity field from the PATTERN network with the product from a C-band radar operated by the German Meteorological Service indicates high spatial accordance of both systems in the geographical position of the rain event as well as reflectivity maxima. Long-term statistics from May to September 2013 prove very good accordance of the X-band radar of the network with C-band radar, but, especially at the border of precipitation events, higher-resolved X-band radar measurements provide more detailed information on precipitation structure because the 1 km range gate of C-band radars is only partially covered with rain. The standard deviation within a range gate of the C-band radar with a range resolution of 1 km is up to 3 dBZ at the borders of rain events. The probability of detection is at least 90%, the false alarm ratio less than 10% for both systems. Therefore, a network of high-resolution low-cost LAWRs can give valuable information on the small-scale structure of rain events in areas of special interest, e.g. urban regions, in addition to the nationwide radar networks.

  6. The Polarimetric Radar Estimation of Rainfall over the Amazon during TRMM-LBA

    NASA Astrophysics Data System (ADS)

    Carey, L. D.; Cifelli, R.; Petersen, W. A.; Rutledge, S. A.

    2002-05-01

    The Tropical Rainfall Measuring Mission (TRMM) is a NASA satellite project initiated to address a gap in our ability to accurately observe detailed rainfall patterns over the tropical continents and oceans. To support TRMM, several field campaigns were conducted. The TRMM-LBA (Large-scale Biosphere Atmosphere) experiment was conducted over the southwestern region of the Amazon (state of Rondonia, Brazil) in order to provide detailed information on the precipitation characteristics in the interior of a tropical continent. Information from TRMM-LBA will be used for validation of TRMM satellite products and for initialization and validation of cloud-resolving models and passive microwave retrieval algorithms. During the TRMM-LBA field campaign, a variety of instrumentation was deployed during the wet season (January - February 1999) to measure rainfall including several rain gauge networks, disdrometers, and the S-band polarimetric (NCAR S-POL) research radar. The focus of this study will be on the estimation, validation, and uncertainty of rain rate estimates derived from the NCAR S-POL radar. The S-POL data were carefully corrected for the presence of clear-air echo, ground clutter, anomalous propagation, partial beam blocking, precipitation attenuation, and calibration biases by applying polarimetric radar methods. Using an optimal polarimetric radar technique, maps of rain rate have been calculated from observations of S-POL horizontal reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) every ten minutes from 10 January to 28 February 1999. From these rain rate estimates, daily and 30-day rain accumulation maps have been compiled. When validated against the rain gauge totals, preliminary S-POL estimates of monthly rainfall, which utilized the equilibrium raindrop shape model of Beard and Chuang (1987), have a negative bias error in the range of -5% to -11% and a standard error of 14% to 20%. We will compare these results with the methodology of Gorgucci et al. (2000, 2001), which attempts to account for the variability in the raindrop shape-size relation. Some practical issues involved in the implementation of this method will be discussed. Finally, we will present preliminary attempts to estimate the uncertainty of the rain rates at each grid point following Bringi and Chandrasekar (2001, Ch. 8). As in BC2001, the uncertainty will be expressed as the standard deviation of R divided by R (σ (R)/R). The uncertainty will be based on 1) the polarimetric algorithm and measurements utilized in the optimal rain rate approach at each point, 2) an estimate of error associated with measurement error as a function of rain rate, and 3) an estimate of the error associated with the utilized algorithm as a function of rain rate. Since there is inherent ambiguity in estimating uncertainty in this manner, we will also experiment with converting σ (R)/R into a qualitative uncertainty index (UI) ranging from 1 to 5, where 1 is very certain and 5 is very uncertain.

  7. A spatial daily rainfall model for interpolation of raingauge networks using artificial radar fields, for realistic hydrological modelling

    NASA Astrophysics Data System (ADS)

    Pegram, Geoff; Gyasi-Agyei, Yeboah

    2014-05-01

    The inherent patchiness and intermittency of daily rainfall make interpolation of sparse point measurements over a catchment very challenging. Usual methods of interpolation of daily rainfall vary from simple numerical averaging through the use of Thiessen polygons to advanced statistical methods such as Kriging. This presentation treats the interpolation problem by conditioning plausible replicas of radar-rainfields on to the point observations and examines the effectiveness of the process by cross-validation. The issues addressed include: * we use Kriging but we first Gaussianise the point rainfall data with special treatment of the zeros to eliminate skewness * Kriging gives us estimates of error in the Gaussian domain to show how good/bad are the interpolations and also offers the standard deviation at each pixel in the field * we choose the form of the [co]variogram to be used in Kriging so as to mimic nature, by using spatial observations given us by radar * the spatial structure of radar rainfall images is peculiar to the accumulation time: instantaneous radar images do not have appreciable spatial anisotropy * by contrast, morphed hourly and daily accumulations of radar images exhibit strong spatial anisotropy * we determine the characteristics of the daily accumulations of radar rainfall and find the spatial correlogram characteristics [orientation, range and ratio of minor to major axes] in the chosen region are strongly related to the radar wetted area ratio: RWAR * to proceed, we simulate correlograms for the chosen day based on the RWAR which is related to the gauge wetness ratio * simulate Gaussian radar fields based on the RWAR with the same variance as the Kriged interpolations of the point values and conditionally merge them with the gauge values, be they observations or simulations * to evaluate the worth of the process, we perform cross-validation of spatial field estimates against gauge values in 'leave-one-out' exercises * the methodology is designed to give a measure of the hydrological response's sensitivity to the uncertainty of spatial interpolation of gauge network rainfall [observed or simulated] by simulating many conditioned spatial replicates, each of which is plausible

  8. Improvement of forecast skill for severe weather by merging radar-based extrapolation and storm-scale NWP corrected forecast

    NASA Astrophysics Data System (ADS)

    Wang, Gaili; Wong, Wai-Kin; Hong, Yang; Liu, Liping; Dong, Jili; Xue, Ming

    2015-03-01

    The primary objective of this study is to improve the performance of deterministic high resolution rainfall forecasts caused by severe storms by merging an extrapolation radar-based scheme with a storm-scale Numerical Weather Prediction (NWP) model. Effectiveness of Multi-scale Tracking and Forecasting Radar Echoes (MTaRE) model was compared with that of a storm-scale NWP model named Advanced Regional Prediction System (ARPS) for forecasting a violent tornado event that developed over parts of western and much of central Oklahoma on May 24, 2011. Then the bias corrections were performed to improve the forecast accuracy of ARPS forecasts. Finally, the corrected ARPS forecast and radar-based extrapolation were optimally merged by using a hyperbolic tangent weight scheme. The comparison of forecast skill between MTaRE and ARPS in high spatial resolution of 0.01° × 0.01° and high temporal resolution of 5 min showed that MTaRE outperformed ARPS in terms of index of agreement and mean absolute error (MAE). MTaRE had a better Critical Success Index (CSI) for less than 20-min lead times and was comparable to ARPS for 20- to 50-min lead times, while ARPS had a better CSI for more than 50-min lead times. Bias correction significantly improved ARPS forecasts in terms of MAE and index of agreement, although the CSI of corrected ARPS forecasts was similar to that of the uncorrected ARPS forecasts. Moreover, optimally merging results using hyperbolic tangent weight scheme further improved the forecast accuracy and became more stable.

  9. A TRMM Precipitation Radar-Calibrated Passive Microwave Algorithm for Overland Rainfall Estimation

    NASA Astrophysics Data System (ADS)

    Dinku, T.; Anagnostou, E. N.

    2004-05-01

    The Tropical Rainfall Measuring Mission (TRMM) satellite carries a combination of active (Precipitation Radar, PR) and multi-channel TRMM microwave imager (TMI) sensors. These sensors advance our ability to estimate rainfall over land. Rain retrieval from PR is associated with an unprecedented accuracy. The primary aspects of PR retrieval are the precipitation classification, which is facilitated by the high vertical resolution (250 meters) reflectivity profile measurements, and an inversion algorithm controlled by a surface reference technique for path integrated attenuation and a reflectivity-to-rainfall relationship with parameters differentiated for convective and stratiform rain regimes. But is limited in terms of sampling due to the narrow PR swath width (215 km). On the other hand, TMI provides wider coverage (760 km), but its observations are associated with a more complex relationship to precipitation compared to PR (especially over land). PR rain estimates are used here for calibrating an overland TMI rain algorithm. The major objective is to investigate the regional variability in terms of the retrieval parameters and its significance to the accuracy of rain estimation. Four geographic regions consisting of Africa (AFC), Amazon (AMZ), continental US (USA), and the Ganges-Brahmaputra-Meghna (GBM) river basin in South Asia are selected. A parameter based rain algorithm is developed that includes (1) multi-channel based rain screening and convective/stratiform (C/S) classification schemes, and (2) non-linear (linear) regressions for rain rate retrieval of stratiform (convective) rain regimes. For rain rate estimation we used the 37 GHz channel for AFC, AMZ and USA regions and the 85 GHz channel for GBM region. The algorithm performance is evaluated against the latest (Version 6) TRMM-2A12 product in terms of rain detection and rain rate retrieval error statistics using PR rainfall as reference. The algorithm performs better than 2A12 V6 with the major improvement being the decrease in the retrieval error variance (correlation to PR rainfall), which is about 40% for three of the regions (USA, AFC and AMZ) and 167% for GBM. Comparison of a global versus regionally varied calibration has yielded varying performance dependence on regional calibration. Specifically, the regional calibration significance on the retrieval accuracy is low for two of the regions (AFC and USA), while moderate and high for AMZ and GBM, respectively. These differences are ascribed to differences in convective activity, particularly differences above the freezing level and ice scattering regime. This study also stresses the importance of convective/stratiform rain type classification in the accuracy of PM retrievals.

  10. 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.

  11. Rainfall threshold definition using an entropy decision approach and radar data

    NASA Astrophysics Data System (ADS)

    Montesarchio, V.; Ridolfi, E.; Russo, F.; Napolitano, F.

    2011-07-01

    Flash flood events are floods characterised by a very rapid response of basins to storms, often resulting in loss of life and property damage. Due to the specific space-time scale of this type of flood, the lead time available for triggering civil protection measures is typically short. Rainfall threshold values specify the amount of precipitation for a given duration that generates a critical discharge in a given river cross section. If the threshold values are exceeded, it can produce a critical situation in river sites exposed to alluvial risk. It is therefore possible to directly compare the observed or forecasted precipitation with critical reference values, without running online real-time forecasting systems. The focus of this study is the Mignone River basin, located in Central Italy. The critical rainfall threshold values are evaluated by minimising a utility function based on the informative entropy concept and by using a simulation approach based on radar data. The study concludes with a system performance analysis, in terms of correctly issued warnings, false alarms and missed alarms.

  12. 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

  13. 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 extension of the 3D composite to all of Germany is therefore possible and set as a goal.

  14. Flight investigation of helicopter IFR approaches to oil rigs using airborne weather and mapping radar

    NASA Technical Reports Server (NTRS)

    Bull, J. S.; Hegarty, D. M.; Phillips, J. D.; Sturgeon, W. R.; Hunting, A. W.; Pate, D. P.

    1979-01-01

    Airborne weather and mapping radar is a near-term, economical method of providing 'self-contained' navigation information for approaches to offshore oil rigs and its use has been rapidly expanding in recent years. A joint NASA/FAA flight test investigation of helicopter IFR approaches to offshore oil rigs in the Gulf of Mexico was initiated in June 1978 and conducted under contract to Air Logistics. Approximately 120 approaches were flown in a Bell 212 helicopter by 15 operational pilots during the months of August and September 1978. The purpose of the tests was to collect data to (1) support development of advanced radar flight director concepts by NASA and (2) aid the establishment of Terminal Instrument Procedures (TERPS) criteria by the FAA. The flight test objectives were to develop airborne radar approach procedures, measure tracking errors, determine accpetable weather minimums, and determine pilot acceptability. Data obtained will contribute significantly to improved helicopter airborne radar approach capability and to the support of exploration, development, and utilization of the Nation's offshore oil supplies.

  15. Results of the Kansas City 1989 Terminal Doppler Weather Radar (TDWR) operational evaluation testing

    NASA Astrophysics Data System (ADS)

    Evans, J. E.

    1990-08-01

    The Terminal Doppler Weather Radar (TDWR) testbed was used at the Kansas City International (KCI) airport during the summer of 1989. The objective was to test and refine previous tested techniques for the automatic detection of low-altitude wind shear phenomena (specifically microbursts and gun fronts) and heavy precipitation in a midwest weather environment, as well as to assess possible new products such as storm movement predictions. A successful operation evaluation of the TDWR products took place at the KCI tower and terminal radar control room (TRACON). Several supervisor and controller display refinements were assessed as effective. The system was successful in terms of aircraft at KCI avoiding wind shear encounters during the operational period, and it was assessed as very good in usefulness for continuing operation by the KCI air traffic control (ATC) personnel. The probability of detection for microbursts was substantially better than that in Denver. However, the false-alarm probability was found to be substantially higher in Kansas City due to a combination of weather and clutter phenomena. By optimizing the site-adaptation capabilities of the TDWR meteorological and data quality algorithms, the required false-alarm probability was achieved. The gust front performance was generally poorer than in Denver due to a combination of unfavorable radar-airport-gust front geometry of false alarms induced by low-level jets. Gust front algorithm refinements which should provide improved performance are discussed.

  16. Forward Looking Radar Imaging by Truncated Singular Value Decomposition and Its Application for Adverse Weather Aircraft Landing

    PubMed Central

    Huang, Yulin; Zha, Yuebo; Wang, Yue; Yang, Jianyu

    2015-01-01

    The forward looking radar imaging task is a practical and challenging problem for adverse weather aircraft landing industry. Deconvolution method can realize the forward looking imaging but it often leads to the noise amplification in the radar image. In this paper, a forward looking radar imaging based on deconvolution method is presented for adverse weather aircraft landing. We first present the theoretical background of forward looking radar imaging task and its application for aircraft landing. Then, we convert the forward looking radar imaging task into a corresponding deconvolution problem, which is solved in the framework of algebraic theory using truncated singular decomposition method. The key issue regarding the selecting of the truncated parameter is addressed using generalized cross validation approach. Simulation and experimental results demonstrate that the proposed method is effective in achieving angular resolution enhancement with suppressing the noise amplification in forward looking radar imaging. PMID:26094627

  17. Forward Looking Radar Imaging by Truncated Singular Value Decomposition and Its Application for Adverse Weather Aircraft Landing.

    PubMed

    Huang, Yulin; Zha, Yuebo; Wang, Yue; Yang, Jianyu

    2015-01-01

    The forward looking radar imaging task is a practical and challenging problem for adverse weather aircraft landing industry. Deconvolution method can realize the forward looking imaging but it often leads to the noise amplification in the radar image. In this paper, a forward looking radar imaging based on deconvolution method is presented for adverse weather aircraft landing. We first present the theoretical background of forward looking radar imaging task and its application for aircraft landing. Then, we convert the forward looking radar imaging task into a corresponding deconvolution problem, which is solved in the framework of algebraic theory using truncated singular decomposition method. The key issue regarding the selecting of the truncated parameter is addressed using generalized cross validation approach. Simulation and experimental results demonstrate that the proposed method is effective in achieving angular resolution enhancement with suppressing the noise amplification in forward looking radar imaging. PMID:26094627

  18. Relationship Among High Rainfall Rates, Atmospheric Moisture, and Temperature Based on High-Resolution Radar-Based Precipitation Estimates

    NASA Astrophysics Data System (ADS)

    Stevens, S. E.; Nelson, B. R.; Kunkel, K.; Prat, O. P.; Karl, T. R.

    2014-12-01

    Global warming is expected to increase maximum rainfall rates in many areas. A primary factor for this expectation is the large increase in atmospheric water vapor content expected with global warming, a simple application of the Clausius-Clapeyron (C-C) relationship. However, the spatial variations of changes will also be modulated by changes in frequency, intensity and location of the storms that produce heavy rainfall. In this study, we explore one dimension of this complex issue, specifically the observational evidence for robust relationships among atmospheric temperature, total precipitable water, and the most extreme magnitudes of surface rainfall rates. We investigate the extent to which a C-C relationship is followed and whether this is dependent on rainstorm duration. This information is crucial to understanding how to incorporate climate change considerations into extreme rainfall design values. Using high-frequency rainfall measurements from both in-situ networks such as the US Climate Reference Network (USCRN) and radar estimates such as the newly-developed National Mosaic and Multisensor Quantitative Precipitation Estimate (NMQ/Q2), rainfall rates and accumulations are compared to precipitable water estimates obtained from both radiosonde data and hourly gridded model analysis. A variety of durations are explored to determine if rising temperature, and thus rising precipitable water availability, corresponds to an increase in the most extreme values of short-term rainfall intensity, longer-term rainfall accumulation, both, or neither.

  19. Performance of high-resolution X-band weather radar networks - the PATTERN example

    NASA Astrophysics Data System (ADS)

    Lengfeld, K.; Clemens, M.; Münster, H.; Ament, F.

    2014-08-01

    This publication intends to proof that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the project Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) observing precipitation with temporal resolution of 30 s, azimuthal resolution of 1° and spatial resolution of 60 m. The network covers an area of 60 km × 80 km. In this paper algorithms used to obtain undisturbed precipitation fields from raw reflectivity data are described and their performance is analysed. In order to correct for background noise in reflectivity measurements operationally, noise level estimates from the measured reflectivity field is combined with noise levels from the last 10 time steps. For detection of non-meteorological echoes two different kinds of clutter filters are applied: single radar algorithms and network based algorithms that take advantage of the unique features of high temporal and spatial resolution of the network. Overall the network based clutter filter works best with a detection rate of up to 70%, followed by the classic TDBZ filter using the texture of the logarithmic reflectivity field. A comparison of a reflectivity field from the PATTERN network with the product from a C-band radar operated by the German Meteorological Service indicates high spatial accordance of both systems in geographical position of the rain event as well as reflectivity maxima. A longterm study derives good accordance of X-band radar of the network with C-band radar. But especially at the border of precipitation events the standard deviation within a range gate of the C-band radar with range resolution of 1 km is up to 3 dBZ. Therefore, a network of high-resolution low-cost LAWRs can give valuable information on the small scale structure of rain events in areas of special interest, e.g. urban regions, in addition the nationwide radar networks.

  20. Under the Weather: Health, Schooling, and Economic Consequences of Early-Life Rainfall. NBER Working Paper No. 14031

    ERIC Educational Resources Information Center

    Maccini, Sharon L.; Yang, Dean

    2008-01-01

    How sensitive is long-run individual well-being to environmental conditions early in life? This paper examines the effect of weather conditions around the time of birth on the health, education, and socioeconomic outcomes of Indonesian adults born between 1953 and 1974. We link historical rainfall for each individual's birth-year and…

  1. Statistical modelling of rainfall-induced shallow landsliding using static predictors and numerical weather predictions: preliminary results

    NASA Astrophysics Data System (ADS)

    Capecchi, V.; Perna, M.; Crisci, A.

    2015-01-01

    Our study is aimed at estimating the added value provided by Numerical Weather Prediction (NWP) data for the modelling and prediction of rainfall-induced shallow landslides. We implemented a quantitative indirect statistical modelling of such phenomena by using, as input predictors, both geomorphological, geological, climatological information and numerical data obtained by running a limited-area weather model. Two standard statistical techniques are used to combine the predictor variables: a generalized linear model and Breiman's random forests. We tested these models for two rainfall events that occurred in 2011 and 2013 in Tuscany region (central Italy). Modelling results are compared with field data and the forecasting skill is evaluated by mean of sensitivity-specificity receiver operating characteristic (ROC) analysis. In the 2011 rainfall event, the random forests technique performs slightly better than generalized linear model with area under the ROC curve (AUC) values around 0.91 vs. 0.84. In the 2013 rainfall event, both models provide AUC values around 0.7. Using the variable importance output provided by the random forests algorithm, we assess the added value carried by numerical weather forecast. The main results are as follows: (i) for the rainfall event that occurred in 2011 most of the NWP data, and in particular hourly rainfall intensities, are classified as "important" and (ii) for the rainfall event that occurred in 2013 only NWP soil moisture data in the first centimetres below ground is found to be relevant for landslide assessment. In the discussions we argue how these results are connected to the type of precipitation observed in the two events.

  2. Application of Attenuation Correction to Precipitation Rates Derived From Terminal Doppler Weather Radar Reflectivity

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Ding, F.; Kitzmiller, D. H.

    2011-12-01

    The Federal Aviation Administration Terminal Doppler Weather Radars (TDWRs) are C band radars that offer high spatio-temporal resolution coverage over major urban areas in the United States. The National Oceanic and Atmospheric Administration, National Weather Service (NWS) has been investigating the incorporation of TDWR data for producing quantitative precipitation estimates to serve its flash and river forecast missions. As reflectivity from C-band Radars can be considerably attenuated by hydrometeors, the NWS Office of Hydrologic Development implemented an algorithm for mitigating this attenuation. In this algorithm, TDWR reflectivity is adjusted iteratively along each radial based on reflectivity and temperature data with the assumption of gamma distribution of drop size. This paper describes the concept and the implementation of the attenuation correction algorithm, and presents a series of validation case studies to examine the impacts of the correction on the accuracy of resulting radar-only QPEs during warm and cool season storm events. Serving as the validation reference is the Stage IV gauge-radar QPE produced by NWS. In order to determine the effects of ingesting spatially variable atmospheric temperature, spatially variable (3-dimensional) temperature from the Rapid Update Cycle 2 (RUC2) model is ingested, and the results are comparatively assessed along with those obtained using spatially averaged surface RUC2 temperatures. Finally, several atmospheric temperature thresholds were tested to avoid over-correction in cases with bright band enhancement. It was found that attenuation correction generally improved correlations between TDWR and StageIV precipitation estimates. The use of low-temperature cutoff criteria appeared effective in minimizing over-correction of attenuation within and beyond the bright band.

  3. Turbulence as observed by concurrent measurements made at NSSL using weather radar, Doppler radar, Doppler lidar and aircraft

    NASA Technical Reports Server (NTRS)

    Lee, Jean T.

    1987-01-01

    As air traffic increases and aircraft capability increases in range and operating altitude, the exposure to weather hazards increases. Turbulence and wind shears are two of the most important of these hazards that must be taken into account if safe flight operations are to be accomplished. Beginning in the early 1960's, Project Rough Rider began thunderstorm investigations. Past and present efforts at the National Severe Storm Laboratory (NSSL) to measure these flight safety hazards and to describe the use of Doppler radar to detect and qualify these hazards are summarized. In particular, the evolution of the Doppler-measured radial velocity spectrum width and its applicability to the problem of safe flight is presented.

  4. Effects of Uncertainty in TRMM Precipitation Radar Path Integrated Attenuation on Interannual Variations of Tropical Oceanic Rainfall

    NASA Technical Reports Server (NTRS)

    Robertson, Franklin R.; Fitzjarrald, Dan E.; Kummerow, Christian D.; Arnold, James E. (Technical Monitor)

    2002-01-01

    Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30 deg N/S) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Time series of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM Precipitation Radar (PR) over the tropical oceans show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. We show that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series. Further analysis of the frequency distribution of PR (2A25 product) rain rates suggests that the algorithm incorporates the attenuation measurement in a very conservative fashion so as to optimize the instantaneous rain rates. Such an optimization appears to come at the expense of monitoring interannual climate variability.

  5. Using NEXRAD Radar Rainfall to Calibrate a Development Impact Model in a Coastal Watershed

    NASA Astrophysics Data System (ADS)

    Sebastian, A.; Bedient, P.

    2012-12-01

    Low slopes and shallow, impermeable soils are characteristic of the Upper Texas Gulf Coast. These, coupled with large rainfall events, contribute to wide floodplains and ponding. Rapid, high intensity development has further exacerbated flooding in this coastal region. The Clear Creek Watershed is located in southeast Houston and empties into Galveston Bay. During the past decade, the watershed has been impacted by significant historical coastal storms and rainfall events such as Tropical Storm Allison (2001), Hurricane Ike (2008), and the April 2009 Event. In this study, we employ a calibrated, distributed hydrologic model and pre- and LID-development models to analyze how development characteristics have contributed to costly flooding in coastal watersheds. In 2012, Brody et al. used FEMA floodclaims collected over the 11-year period between 1999 and 2009 to examine the pattern of flood loss across the Clear Creek watershed. The results showed that the 100-year floodplain did not adequately represent overall or event-specific loss. Using a spatial cluster analysis, the Turkey Creek sub-area of the Clear Creek watershed was pin-pointed as an area of statistically significant flood loss, an area where there were a considerable number of high-value flood claims. This area is characterized by high-density, poorly constructed development and frequent flooding. In parallel with Brody's study of flood-risk indicators, our study aims to examine the behavior of the flood-wave in the coastal watershed and how it is affected by different development patterns. A distributed hydrologic VfloTM model was built for Turkey Creek using 2008 CCAP land cover data and calibrated using NEXRAD radar rainfall for the Hurricane Ike (2008) and April 2009 events. Once the model was calibrated, both pre- and LID-development models were built using historical land cover data. These models were used to identify how development patterns have influence the flood hydrograph. Early results indicate that the construction of impervious surfaces has greatly increased the flood peak and shortened the time to peak of the flood wave. The study will go further to identify the measures that may be taken to reduce flooding in the Clear Creek Watershed and attempt to extrapolate the best management practices for low impact development in coastal watersheds.

  6. Improving Tornado Warnings with the Federal Aviation Administration's Terminal Doppler Weather Radar.

    NASA Astrophysics Data System (ADS)

    Vasiloff, Steven V.

    2001-05-01

    The potential role of the Federal Aviation Administration's Terminal Doppler Weather Radar (TDWR) to supplement the Weather Surveillance Radar-1988 Doppler (WSR-88D) for tornado detection is discussed. Compared to the WSR-88D, the TDWR has a narrower beam, lower scan angles, and faster update rates. The 11 August 1999 Salt Lake City, Utah, tornado is used as an illustration of the utility of the TDWR. The Salt Lake City TDWR was much closer to the tornado than the WSR-88D and the WSR-88D was 750 m higher than the TDWR. Because the tornado developed rapidly upward from a surface convergence line, the TDWR detected the formation earlier than the WSR-88D. Also, the vortex signatures associated with the tornado were much better defined by the TDWR.The enhanced spatial and temporal coverage provided by the TDWR network is shown. A significant improvement in tornado detection, as well as other low-altitude phenomena, would be gained. However, ground clutter and signal attenuation can degrade coverage. Ongoing efforts by the National Weather Service to incorporate TDWR data into operations are described.

  7. Weak linkage between the heaviest rainfall and tallest storms

    NASA Astrophysics Data System (ADS)

    Hamada, Atsushi; Takayabu, Yukari N.; Liu, Chuntao; Zipser, Edward J.

    2015-02-01

    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection.

  8. Weak linkage between the heaviest rainfall and tallest storms

    PubMed Central

    Hamada, Atsushi; Takayabu, Yukari N.; Liu, Chuntao; Zipser, Edward J.

    2015-01-01

    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. PMID:25708295

  9. Weak linkage between the heaviest rainfall and tallest storms.

    PubMed

    Hamada, Atsushi; Takayabu, Yukari N; Liu, Chuntao; Zipser, Edward J

    2015-01-01

    Conventionally, the heaviest rainfall has been linked to the tallest, most intense convective storms. However, the global picture of the linkage between extreme rainfall and convection remains unclear. Here we analyse an 11-year record of spaceborne precipitation radar observations and establish that a relatively small fraction of extreme convective events produces extreme rainfall rates in any region of the tropics and subtropics. Robust differences between extreme rainfall and convective events are found in the rainfall characteristics and environmental conditions, irrespective of region; most extreme rainfall events are characterized by less intense convection with intense radar echoes not extending to extremely high altitudes. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Our results demonstrate that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. PMID:25708295

  10. Urban rainfall estimation employing commercial microwave links

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire

    2015-04-01

    Urban areas often lack rainfall information. To increase the number of rainfall observations in cities, microwave links from operational cellular telecommunication networks may be employed. Although this new potential source of rainfall information has been shown to be promising, its quality needs to be demonstrated more extensively. In the Rain Sense kickstart project of the Amsterdam Institute for Advanced Metropolitan Solutions (AMS), sensors and citizens are preparing Amsterdam for future weather. Part of this project is rainfall estimation using new measurement techniques. Innovative sensing techniques will be utilized such as rainfall estimation from microwave links, umbrellas for weather sensing, low-cost sensors at lamp posts and in drainage pipes for water level observation. These will be combined with information provided by citizens in an active way through smartphone apps and in a passive way through social media posts (Twitter, Flickr etc.). Sensor information will be integrated, visualized and made accessible to citizens to help raise citizen awareness of urban water management challenges and promote resilience by providing information on how citizens can contribute in addressing these. Moreover, citizens and businesses can benefit from reliable weather information in planning their social and commercial activities. In the end city-wide high-resolution rainfall maps will be derived, blending rainfall information from microwave links and weather radars. This information will be used for urban water management. This presentation focuses on rainfall estimation from commercial microwave links. Received signal levels from tens of microwave links within the Amsterdam region (roughly 1 million inhabitants) in the Netherlands are utilized to estimate rainfall with high spatial and temporal resolution. Rainfall maps will be presented and compared to a gauge-adjusted radar rainfall data set. Rainfall time series from gauge(s), radars and links will be compared.

  11. The pulse-pair algorithm as a robust estimator of turbulent weather spectral parameters using airborne pulse Doppler radar

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

    The pulse pair method for spectrum parameter estimation is commonly used in pulse Doppler weather radar signal processing since it is economical to implement and can be shown to be a maximum likelihood estimator. With the use of airborne weather radar for windshear detection, the turbulent weather and strong ground clutter return spectrum differs from that assumed in its derivation, so the performance robustness of the pulse pair technique must be understood. Here, the effect of radar system pulse to pulse phase jitter and signal spectrum skew on the pulse pair algorithm performance is discussed. Phase jitter effect may be significant when the weather return signal to clutter ratio is very low and clutter rejection filtering is attempted. The analysis can be used to develop design specifications for airborne radar system phase stability. It is also shown that the weather return spectrum skew can cause a significant bias in the pulse pair mean windspeed estimates, and that the poly pulse pair algorithm can reduce this bias. It is suggested that use of a spectrum mode estimator may be more appropriate in characterizing the windspeed within a radar range resolution cell for detection of hazardous windspeed gradients.

  12. Weather types across the Caribbean basin and their relationship with rainfall and sea surface temperature

    NASA Astrophysics Data System (ADS)

    Moron, Vincent; Gouirand, Isabelle; Taylor, Michael

    2015-10-01

    Eight weather types (WTs) are computed over 98.75°W-56.25°W, 8.75°N-31.25°N using cluster analysis of daily low-level (925 hPa) winds and outgoing longwave radiation, without removing the mean annual cycle, by a k-means algorithm from 1979 to 2013. The WTs can be firstly interpreted as snapshots of the annual cycle with a clear distinction between 5 "wintertime" and 3 "summertime" WTs, which account together for 70 % of the total mean annual rainfall across the studied domain. The wintertime WTs occur mostly from late November to late April and are characterized by varying intensity and location of the North Atlantic subtropical high (NASH) and transient synoptic troughs along the northern edge of the domain. Large-scale subsidence dominates the whole basin but rainfall can occur over sections of the basin, especially on the windward shores of the troughs associated with the synoptic waves. The transition between wintertime and summertime WTs is rather abrupt, especially in May. One summertime WT (WT 4) is prevalent in summer, and almost exclusive around late July. It is characterized by strong NASH, fast Caribbean low level jet and rainfall mostly concentrated over the Caribbean Islands, the Florida Peninsula, the whole Central America and the tropical Eastern Pacific. The two remaining summertime WTs display widespread rainfall respectively from Central America to Bermuda (WT 5) and over the Eastern Caribbean (WT 6). Both WTs combine reduced regional scale subsidence and weaker Caribbean low-level jet relatively to WT 4. The relationships between WT frequency and El Niño Southern Oscillation (ENSO) events are broadly linear. Warm central and eastern ENSO events are associated with more WT 4 (less WT 5-6) during boreal summer and autumn (0) while this relationship is reversed during boreal summer (+1) for central events only. In boreal winter, the largest anomalies are observed for two WTs consistent with negative (WT 2) and positive (WT 8) phases of the North Atlantic Oscillation; more (less) WT 2 and less (more) WT 8 than usually occur from January to early April during warm (cold) ENSO events, the strongest anomalies being recorded during eastern events. Multinomial logistic regression is used to hindcast the 11-day low-pass filtered occurrence of WTs from local (Caribbean Sea and Gulf of Mexico) and remote (Eastern and Central Tropical Pacific) sea surface temperatures (SSTs). In boreal summer, the interannual variability of the seasonal occurrence of WTs 4-6 is well hindcast when at least the Caribbean Sea and Eastern Tropical Pacific are included as predictors with anomalously warm (cold) SSTs over the Caribbean Sea (Eastern Tropical Pacific) being related to more WT 5-6 and less WT 4 and vice-versa. Using antecedent SST to forecast WT frequency shows that the SST forcing is negligible at the start of boreal summer and increases toward its end.

  13. Cockpit weather radar display demonstrator and ground-to-air sferics telemetry system

    NASA Technical Reports Server (NTRS)

    Nickum, J. D.; Mccall, D. L.

    1982-01-01

    The results of two methods of obtaining timely and accurate severe weather presentations in the cockpit are detailed. The first method described is a course up display of uplinked weather radar data. This involves the construction of a demonstrator that will show the feasibility of producing a course up display in the cockpit of the NASA simulator at Langley. A set of software algorithms was designed that could easily be implemented, along with data tapes generated to provide the cockpit simulation. The second method described involves the uplinking of sferic data from a ground based 3M-Ryan Stormscope. The technique involves transfer of the data on the CRT of the Stormscope to a remote CRT. This sferic uplink and display could also be included in an implementation on the NASA cockpit simulator, allowing evaluation of pilot responses based on real Stormscope data.

  14. Terminal Doppler Weather Radar (TDWR) build 5 Test and Evaluation Master Plan (TEMP)

    NASA Astrophysics Data System (ADS)

    Turcich, Elizabeth; Cranston, Robert

    1994-05-01

    This document presents the Terminal Doppler Weather Radar (TDWR), Build 5 enhancement, Test and Evaluation Master Plan (TEMP). This Build 5 TEMP identifies Operational Test and Evaluation (OT&E) objectives, responsibilities, resources, schedules, and critical test issues. The Build 5 enhancement consists of a Build 5A which provides connectivity to the Low Level Wind Shear Alert System (LLWAS) 2, and a Build 5B which provides connectivity to an LLWAS III. Build 5A displays LLWAS 2 wind data along with TDWR hazardous weather data on TDWR Geographic Situation Displays (GSD) and Ribbon Display Terminals (RDT). Build 5B provides additional capabilities such as having a Microburst Shear Integration Algorithm (MSIA), TDWR/LLWAS 3 Integration Algorithm, 15-day archiving and TDWR, LLWAS 2 and LLWAS 3 data integration.

  15. Dual-polarization C-band weather radar algorithms for rain rate estimation and hydrometeor classification in an alpine region

    NASA Astrophysics Data System (ADS)

    Paulitsch, H.; Teschl, F.; Randeu, W. L.

    2009-03-01

    Dual polarization is becoming the standard for new weather radar systems. 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. Since hydrometeors are often far from being spherical, the backscatter and propagation are different for horizontal and vertical polarization. Comparing the reflected horizontal and vertical power returns and their ratio and correlation, information on size, shape, and material density of cloud and precipitation particles can be obtained. The use of polarimetric radar variables can therefore increase the accuracy of the rain rate estimation compared to standard Z-R relationships of non-polarimetric radars. It is also possible to derive the type of precipitation from dual polarization parameters, although this is not an easy task, since there is no clear discrimination between the different values. Fuzzy logic approaches have been shown to work well with overlapping conditions and imprecisely defined class output. In this paper the implementation of different polarization algorithms for the new Austrian weather radar on Mt. Valluga is described, and first results from operational use are presented. This study also presents first observations of rain events in August 2007 during the test run of the radar. Further, the designated rain rate estimation and hydrometeor classification algorithms are explained.

  16. Ground-based weather radar remote sensing of volcanic ash explosive eruptions

    NASA Astrophysics Data System (ADS)

    Marzano, F. S.; Marchiotto, S.; Barbieri, S.; Giuliani, G.; Textor, C.; Schneider, D. J.

    2009-04-01

    The explosive eruptions of active volcanoes with a consequent formation of ash clouds represent a severe threat in several regions of the urbanized world. During a Plinian or a sub-Plinian eruption the injection of large amounts of fine and coarse rock fragments and corrosive gases into the troposphere and lower stratosphere is usually followed by a long lasting ashfall which can cause a variety of damages. Volcanic ash clouds are an increasing hazard to aviation safety because of growing air traffic volumes that use more efficient and susceptible jet engines. Real-time and areal monitoring of a volcano eruption, in terms of its intensity and dynamics, is not always possible by conventional visual inspections, especially during worse visibility periods which are quite common during eruption activity. Remote sensing techniques both from ground and from space represent unique tools to be exploited. In this respect, microwave weather radars can gather three-dimensional information of atmospheric scattering volumes up several hundreds of kilometers, in all weather conditions, at a fairly high spatial resolution (less than a kilometer) and with a repetition cycle of few minutes. Ground-based radar systems represent one of the best methods for determining the height and volume of volcanic eruption clouds. Single-polarization Doppler radars can measure horizontally-polarized power echo and Doppler shift from which ash content and radial velocity can be, in principle, extracted. In spite of these potentials, there are still several open issues about microwave weather radar capabilities to detect and quantitatively retrieve ash cloud parameters. A major issue is related to the aggregation of volcanic ash particles within the eruption column of explosive eruptions which has been observed at many volcanoes. It influences the residence time of ash in the atmosphere and the radiative properties of the "umbrella" cloud. Numerical experiments are helpful to explore processes occurring in the eruption column. In this study we use the plume model ATHAM (Active Tracer High Resolution Atmospheric Model) to investigate, in both time and space, processes leading to particle aggregation in the eruption column. In this work a set of numerical simulations of radar reflectivity is performed with the ATHAM model, under the same experimental conditions except for the initial size distribution, i.e. varying the radii of average mass of the two particle dimension modes. A sensitivity analysis is carried out to evaluate the possible impact of aggregate particles on microwave radar reflectivity. It is shown how dimension, composition, temperature and mass concentration are the main characteristics of eruptive cloud particles that contribute to determine different radar reflectivity responses. In order to evaluate Rayleigh scattering approximation accuracy, the ATHAM simulations of radar reflectivity are used to compare in a detailed way the Mie and Rayleigh scattering regimes at S-, C- and X-band. The relationship between radar reflectivity factor and ash concentration has been statistically derived for the various particle classes by applying a new radar reflectivity microphysical model, which was developed starting from results of numerical experiments performed with plume model ATHAM. The ash retrieval physical-statistical algorithm is based on the backscattering microphysical model of volcanic cloud particles, used within a Bayesian classification and optimal regression algorithm. In order to illustrate the potential of this microwave active remote sensing technique, the case study of the eruption of Augustine volcano in Alaska in January 2006 is described. This event was the first time that a significant volcanic eruption was observed within the nominal range of a WSR-88D. The radar data, in conjunction with pilot reports, proved to be crucial in analyzing the height and movement of volcanic ash clouds during and immediately following each eruptive event. This data greatly aided National Weather Service meteorologists in the issuance of timely and accurate warning and advisory products to aviation, public, and marine interests. An application of the retrieval technique has been shown, taking into consideration the eruption of the Augustine volcano. Volume scan data from the NEXRAD WSR-88D S-band radar, which are located 190 km from the volcano vent, are processed to identify and estimate the particles concentration in an automatic fashion. The evolution of the Augustine Vulcanian eruption is discussed in terms of radar measurements products, pointing out the unique features, the current limitations and future improvements of radar remote sensing of volcanic plumes.

  17. Accuracy of rainfall measurement for scales of hydrological interest

    NASA Astrophysics Data System (ADS)

    Wood, S. J.; Jones, D. A.; Moore, R. J.

    The dense network of 49 raingauges over the 135 km2 Brue catchment in Somerset, England is used to examine the accuracy of rainfall estimates obtained from raingauges and from weather radar. Methods for data quality control and classification of precipitation types are first described. A super-dense network comprising eight gauges within a 2 km grid square is employed to obtain a "true value" of rainfall against which the 2 km radar grid and a single "typical gauge" estimate can be compared. Accuracy is assessed as a function of rainfall intensity, for different periods of time-integration (15 minutes, 1 hour and 1 day) and for two 8-gauge networks in areas of low and high relief. In a similar way, the catchment gauge network is used to provide the "true catchment rainfall" and the accuracy of a radar estimate (an area-weighted average of radar pixel values) and a single "typical gauge" estimate of catchment rainfall evaluated as a function of rainfall intensity. A single gauge gives a standard error of estimate for rainfall in a 2 km square and over the catchment of 33% and 65% respectively, at rain rates of 4 mm in 15 minutes. Radar data at 2 km resolution give corresponding errors of 50% and 55%. This illustrates the benefit of using radar when estimating catchment scale rainfall. A companion paper (Wood et al., 2000) considers the accuracy of rainfall estimates obtained using raingauge and radar in combination.

  18. Evaluation of X-band polarimetric radar estimation of rainfall and rain drop size distribution parameters in West Africa

    NASA Astrophysics Data System (ADS)

    Koffi, A. K.; Gosset, M.; Zahiri, E.-P.; Ochou, A. D.; Kacou, M.; Cazenave, F.; Assamoi, P.

    2014-06-01

    As part of the African Monsoon Multidisciplinary Analysis (AMMA) field campaign an X-band dual-polarization Doppler radar was deployed in Benin, West-Africa, in 2006 and 2007, together with a reinforced rain gauge network and several optical disdrometers. Based on this data set, a comparative study of several rainfall estimators that use X-band polarimetric radar data is presented. In tropical convective systems as encountered in Benin, microwave attenuation by rain is significant and quantitative precipitation estimation (QPE) at X-band is a challenge. Here, several algorithms based on the combined use of reflectivity, differential reflectivity and differential phase shift are evaluated against rain gauges and disdrometers. Four rainfall estimators were tested on twelve rainy events: the use of attenuation corrected reflectivity only (estimator R(ZH)), the use of the specific phase shift only R(KDP), the combination of specific phase shift and differential reflectivity R(KDP,ZDR) and an estimator that uses three radar parameters R(ZH,ZDR,KDP). The coefficients of the power law relationships between rain rate and radar variables were adjusted either based on disdrometer data and simulation, or on radar-gauges observations. The three polarimetric based algorithms with coefficients predetermined on observations outperform the R(ZH) estimator for rain rates above 10 mm/h which explain most of the rainfall in the studied region. For the highest rain rates (above 30 mm/h) R(KDP) shows even better scores, and given its performances and its simplicity of implementation, is recommended. The radar based retrieval of two parameters of the rain drop size distribution, the normalized intercept parameter NW and the volumetric median diameter Dm was evaluated on four rainy days thanks to disdrometers. The frequency distributions of the two parameters retrieved by the radar are very close to those observed with the disdrometer. NW retrieval based on a combination of ZH-KDP-ZDR works well whatever the a priori assumption made on the drop shapes. Dm retrieval based on ZDR alone performs well, but if satisfactory ZDR measurements are not available, the combination ZH-KDP provides satisfactory results for both Dm and NW if an appropriate a priori assumption on drop shape is made.

  19. Use Of Radar-Rainfall Data for the Southwest Coastal Louisiana Feasibility Study: Regional Scale Hydrologic and Salinity Modeling and Management Scenario Analysis for Chenier Plain

    NASA Astrophysics Data System (ADS)

    Meselhe, E. A.; Michot, B.; Chen, C.; Habib, E. H.

    2011-12-01

    The Chenier Plain, in Southwest Louisiana, extends from Vermilion Bay to Sabine Lake in southeast Texas. It has great economic, industrial, recreational, and ecological value. Over the years, human activities such as dredging ship channels and access canals, building roads, levees, and hydraulic structures have altered the hydrology of the Chenier Plain. These alterations have affected the fragile equilibrium of the marsh ecology. If no action is taken to restore the Chenier Plain, land loss through conversion of marsh to open water would continue. The Southwest Coastal Louisiana Feasibility Study aims at evaluating proposed protection and restoration measures and ultimately submitting a comprehensive plan to protect and preserve the Chenier Plain at the regional scale. The proposed alternatives include marsh creation, terracing, shoreline protection, and freshwater introduction and salinity control structures. A regional scale hydrodynamic and salinity transport model was developed to screen and assess the proposed restoration measures. A critical component of this modeling effort is local rainfall. The strong spatial variability and limited availability of ground-level precipitation measurements limited our ability to capture local rainfall. Thus, a radar-based rainfall product was used as a viable alternative to the rain gauges. These estimates are based on the National Weather Service from the Multi-Sensor Precipitation Estimator (MPE) algorithm. Since the model was used to perform long-term (yearly) simulations, the 4x4 km2 MPE estimates were represented as daily accumulations. The use of the radar-rainfall product data improved the model performance especially on our ability to capture the spatial and temporal variations of salinity. Overall, the model is improving our understanding of the circulation patterns and salinity regimes of the region. The circulation model used here is the MIKE FLOOD software (Danish Hydraulic Institute, DHI 2008) which dynamically integrates a two-dimensional grid (MIKE 21) and a one-dimensional channel flow simulation tool (MIKE 11). The model was successfully calibrated and validated using water level and salinity data collected at monitoring stations in the channels and throughout the marsh areas. The model prediction agreed favorably with the field measurements at the daily and monthly average scale. Uncertainties in the bathymetric data, open water boundary, as well as the operation schedules of water control structures prevented the model from being validated at a higher temporal frequency. Ongoing monitoring efforts are being used to minimize these uncertainties.

  20. Super-resolution technologies for all-weather sense and avoidance (SAA) radar

    NASA Astrophysics Data System (ADS)

    Zhang, Yan Rockee; Li, Zhengzheng; Wang, Shang; Pan, Yu; Suarez, Hernan

    2011-06-01

    The sense and avoidance (SAA) and due-regard radar systems have strict requirements on size, weight and power (SWaP) and target localization accuracies. Also, the multi-mission capabilities with both weather and hard targets are critical to the survivability of unmanned aerial vehicles (UAV) in the next generation national airspace. The aperture limitations of the aircraft sensor installation, however, have prevented large antennas/arrays to be used. The tradeoffs among frequencies, resolutions and detection range/accuracies have not been fully addressed. Innovative concepts of overcoming the aperture limitation by using a special type of super-resolution technology are introduced. The first technique is based on a combination of thinned antenna array, an extension to the traditional Multiple Signal Classification (MUSIC) technique, and applying a two-dimensional sidelobe mitigation technique. To overcome the degradation of MUSIC-type of approach due to coherent radar signals, a special waveform optimization procedure is used. The techniques for mitigating artifacts due to "thinned" array are also introduced. Simulated results of super-resolution techniques are discussed and evaluated, and the capability of separating multiple targets within aperture-constrained beamwidth is demonstrated. Moreover, the potential capabilities of autonomous weather hazard avoidance are also analyzed.

  1. Terminal Doppler Weather Radar (TDWR) observation of atmospheric flow over complex terrain during tropical cyclone passages

    NASA Astrophysics Data System (ADS)

    Shun, Chi M.; Lau, Sharon S. Y.

    2000-12-01

    To facilitate warning of low-level wind shear associated with convective storms, a Terminal Doppler Weather Radar (TWDR) was installed about 12 km to the northeast of the Hong Kong International Airport (HKIA). The HKIA is located just off the northern shore of an island known as Lantau. The HKIA lies on the lee side of the complex terrain of Lantau when winds come from the east through the southwest. With the commissioning of the TDWR in 1997, interesting high-resolution radar data were collected in strong southerly flows during tropical cyclone passages. These data sets reveal the complex low-level atmospheric flow in the vicinity of the HKIA, including streaks of low-speed flow, reverse flows, small-scale vortices and high-speed gap flows. Animation sequences of the radar images suggest existence of von Karman vortex streets and vortex shedding in the wake regions. These phenomena could induce strong shear regions which led to significant low-level wind shear for landing/departing aircraft. Analysis of on-board flight data for a wind shear event experienced by a landing aircraft in strong southeasterly flow revealed that terrain- induced features with horizontal scale less than 1 km brought significant air speed changes to the aircraft over a short duration of time.

  2. Machine intelligent approach to automated gust-front detection for Doppler weather radars

    NASA Astrophysics Data System (ADS)

    Troxel, Seth W.; Delanoy, Richard L.

    1994-07-01

    Automated gust front detection is an important component of the airport surveillance radar with wind shear processor (ASR-9 WSP) and terminal Doppler weather radar (TDWR) systems being developed for airport terminal areas. Gust fronts produce signatures in Doppler radar imagery which are often weak, ambiguous, or conditional, making detection and continuous tracking of gust fronts challenging. A machine intelligent gust front algorithm (MIGFA) has been developed that makes use of two new techniques of knowledge-based signal processing: functional template correlation (FTC), a generalized matched filter incorporating aspects of fuzzy set theory; and the use of `interest' as a medium for pixel-level data fusion. This paper focuses on the more recently developed TDWR MIGFA, describing the signal-processing techniques used and general algorithm design. A quantitative performance analysis using data collected during recent real-time testing of the TDWR MIGFA in Orlando, Florida is also presented. Results show that MIGFA substantially outperforms the gust front detection algorithm used in current TDWR systems.

  3. NEXRAD Weather Radar Observations of the 2006 Augustine Volcanic Eruption Clouds

    NASA Astrophysics Data System (ADS)

    Schneider, D. J.; Scott, C.; Wood, J.; Hall, T.

    2006-12-01

    The 2006 eruption of Augustine Volcano, Alaska provided an exceptional opportunity to detect and measure explosive volcanic events and to track drifting volcanic clouds using WRS-88D (NEXRAD) weather radar data. Radar data complemented the real-time seismic monitoring by providing rapid confirmation of ash generation and cloud height. The explosive phase of the eruption consisted of thirteen discrete Vulcanian explosions from January 11 to 28, with seismic durations that ranged from one to eleven minutes. The ash columns and drifting clouds from all of the events were observed via a NEXRAD located 185 km NE of the volcano on the Kenai Peninsula (site PAHG). The radar was operated in both precipitation and clear air modes, resulting in a temporal resolution of 4.1 to 10 minutes per complete scan, respectively. Scan elevation angles for the radar beam centroid varied slightly depending upon mode of operation, but values of 0.5, 1.5, 2.5, and 3.5 degrees were typically used, corresponding to altitudes over the volcano of 3.8, 7.2, 10.5, and 13.8 km above sea level. Estimates of eruption cloud height were made by the National Weather Service (NWS) Anchorage Forecast Office using range-height indication cross-sections and radar echo tops (the altitude of the +18.5 dBZ reflectance surface). The observed cloud heights typically ranged from 7.5 to 10.5 km above sea level, with the exception of the January 17 event which briefly had an echo top of about 14 km. Most of the eruption clouds reached their maximum height in the first scan in which they were visible, suggesting an energetic and impulsive initial event, and were at lower heights in subsequent views. These height estimates may be minimum values because very fine-grained ash at the top of eruption clouds has low radar reflectance, and thus may not be observed. Height estimates were rapidly communicated to the NWS Alaska Aviation Weather Unit and the Alaska Volcano Observatory for use in hazard statements and related cloud dispersion modeling. Base reflectivity images at four scan angles provided additional insight into the vertical ash distribution. Generally, the eruption column and associated volcanic clouds had the greatest areal coverage and highest reflectivity values (as high as +60 dBZ) at the two lowest scan elevation angles (0.5 and 1.5 degrees or heights of about 3.8 to 7.2 km above sea level). The explosions on January 13 and 17 produced volcanic clouds that propagated upwind for ten to twenty minutes before dispersing, suggesting that some of the ash was being generated by pyroclastic flows on the flanks. Drifting volcanic clouds were tracked in the data for as long as two hours after the start of the eruption, with reflectivity values as low as -4 dBZ observed. Retrospective analyses of level-3 NEXRAD data from the Kenai (PAHG) and King Salmon (PAKC) radars (200 km SW of Augustine) examined radial base velocity and spectrum width (a measure of the velocity variance within a scan volume) at four scan angles. The highest base velocities observed were for the January 17 event, which reached 33 m/s, the maximum value computed by the level-3 algorithm. This event, and similar ones on January 13, were characterized by moderately high spectrum widths (as large as 9.8 m/s), indicative of turbulence and wind shear.

  4. The effect of flow and orography on the spatial distribution of the very short-term predictability of rainfall from composite radar images

    NASA Astrophysics Data System (ADS)

    Foresti, L.; Seed, A.

    2014-11-01

    The spatial distribution and scale dependence of the very short-term predictability of precipitation by Lagrangian persistence of composite radar images is studied under different flow regimes in connection with the presence of orographic features. Data from the weather radar composite of eastern Victoria, Australia, a 500 × 500 km2 domain at 10 min temporal and 2 × 2 km2 spatial resolutions, covering the period from February 2011 to October 2012, were used for the analyses. The scale dependence of the predictability of precipitation is considered by decomposing the radar rainfall field into an eight-level multiplicative cascade using a fast Fourier transform. The rate of temporal development of precipitation in Lagrangian coordinates is estimated at each level of the cascade under different flow regimes, which are stratified by applying a k-means clustering algorithm on the diagnosed velocity fields. The predictability of precipitation is measured by its lifetime, which is derived by integrating the Lagrangian auto-correlation function. The lifetimes were found to depend on the scale of the feature as a power law, which is known as dynamic scaling, and to vary as a function of flow regime. The lifetimes also exhibit significant spatial variability and are approximately a factor of 2 longer on the upwind compared with the downwind slopes of terrain features. The scaling exponent of the spatial power spectrum also shows interesting geographical differences. These findings provide opportunities to perform spatially inhomogeneous stochastic simulations of space-time precipitation to account for the presence of orography, which may be integrated into design storm simulations and stochastic precipitation nowcasting systems.

  5. Interpolation of daily rainfall networks using simulated radar fields for realistic hydrological modelling of spatial rain field ensembles

    NASA Astrophysics Data System (ADS)

    Gyasi-Agyei, Yeboah; Pegram, Geoffrey

    2014-11-01

    Given a record of daily rainfall over a network of gauges, this paper describes a method of linking the Gauge Wetness Ratio (GWR) on a given day to the joint distribution of the parameters of the anisotropic correlogram defining the spatial statistics of simulated radar-rainfall fields. We generate a large number of Gaussian random fields by sampling from the correlogram parameters conditioned on the GWR and then conditionally merge these fields to the gauge observations transformed into the Gaussian domain. Availability of such a tool allows better spatially distributed hydrological modelling, because good quality ensemble spatial information is required for such work, as it yields uncertainty of the fields so generated. To achieve these ends, correlograms of many Gaussianised daily accumulations of radar images were developed using the Fast Fourier Transform to generate their sample power spectra. Empirical correlograms were fitted using a 2D exponential distribution to yield the 3 key parameters of the correlogram: the range, the anisotropy ratio and the direction of the major axis. It was found that the range follows a Gamma distribution while the anisotropy parameters follow a Loglogistic one; a t5 copula was adequate to capture the bivariate negative dependence structure between the range and ratio. The Radar Wetted Area Ratio (RWAR) drives the parameters of the correlogram, and its link with GWR is modelled by a transition probability matrix. We take each of the generated Gaussian random fields and conditionally merge it with Gaussianised rainfall values at the gauge locations using Ordinary Kriging. The method produces realistic simulated radar images, on a grid chosen to suit the data, which match the gauge observations at their locations. Ensemble simulations of 1000 samples were used to derive the median and the inter-quartile range of the fields; these were found to narrow near the control gauge locations, as expected, emphasising the value of high density gauge networks. Ongoing research is looking towards integration of the presented methodology with a stochastic daily rainfall generator for useful spatial rainfall simulation over catchments with gauged records.

  6. Estimation of sea-surface winds using backscatter cross-section measurements from airborne research weather radar

    SciTech Connect

    Hildebrand, P.H. . Remote Sensing Facility)

    1994-01-01

    A technique is presented for estimation of sea-surface winds using backscatter cross-section measurements from an airborne research weather radar. The technique is based on an empirical relation developed for use with satellite-borne microwave scatterometers which derives sea-surface winds from radar backscatter cross-section measurements. Unlike a scatterometer, the airborne research weather radar is a Doppler radar designed to measure atmospheric storm structure and kinematics. Designed to scan the atmosphere, the radar also scans the ocean surface over a wide range of azimuths, with the incidence angle and polarization angle changing continuously during each scan. The new sea-surface wind estimation technique accounts for these variations in incidence angle and polarization and derives the atmospheric surface winds. The technique works well over the range of wind conditions over which the wind speed-backscatter cross-section relation holds, about 2--20 m/s. The problems likely to be encountered with this new technique are evaluated and it is concluded that most problems are those which are endemic to any microwave scatterometer wind estimation technique. The new technique will enable using the research weather radar to provide measurements which would otherwise require use of a dedicated scatterometer.

  7. Ranger© - An Affordable, Advanced, Next-Generation, Dual-Pol, X-Band Weather Radar

    NASA Astrophysics Data System (ADS)

    Stedronsky, Richard

    2014-05-01

    The Enterprise Electronics Corporation (EEC) Ranger© system is a new generation, X-band (3 cm), Adaptive Polarization Doppler Weather Surveillance Radar that fills the gap between high-cost, high-power traditional radar systems and the passive ground station weather sensors. Developed in partnership with the University of Oklahoma Advanced Radar Research Center (ARRC), the system uses relatively low power solid-state transmitters and pulse compression technology to attain nearly the same performance capabilities of much more expensive traditional radar systems. The Ranger© also employs Adaptive Dual Polarization (ADP) techniques to allow Alternating or Simultaneous Dual Polarization capability with total control over the transmission polarization state using dual independent coherent transmitters. Ranger© has been designed using the very latest technology available in the industry and the technical and manufacturing experience gained through over four decades of successful radar system design and production at EEC. The entire Ranger© design concept emphasizes precision, stability, reliability, and value using proven solid state technology combined with the most advanced motion control system ever conceived for weather radar. Key applications include meteorology, hydrology, aviation, offshore oil/gas drilling, wind energy, and outdoor event situational awareness.

  8. Prediction of a Flash Flood in Complex Terrain. Part II: A Comparison of Flood Discharge Simulations Using Rainfall Input from Radar, a Dynamic Model, and an Automated Algorithmic System.

    NASA Astrophysics Data System (ADS)

    Yates, David N.; Warner, Thomas T.; Leavesley, George H.

    2000-06-01

    Three techniques were employed for the estimation and prediction of precipitation from a thunderstorm that produced a flash flood in the Buffalo Creek watershed located in the mountainous Front Range near Denver, Colorado, on 12 July 1996. The techniques included 1) quantitative precipitation estimation using the National Weather Service's Weather Surveillance Radar-1988 Doppler and the National Center for Atmospheric Research's S-band, dual-polarization radars, 2) quantitative precipitation forecasting utilizing a dynamic model, and 3) quantitative precipitation forecasting using an automated algorithmic system for tracking thunderstorms. Rainfall data provided by these various techniques at short timescales (6 min) and at fine spatial resolutions (150 m to 2 km) served as input to a distributed-parameter hydrologic model for analysis of the flash flood. The quantitative precipitation estimates from the weather radar demonstrated their ability to aid in simulating a watershed's response to precipitation forcing from small-scale, convective weather in complex terrain. That is, with the radar-based quantitative precipitation estimates employed as input, the simulated peak discharge was similar to that estimated. The dynamic model showed the most promise in providing a significant forecast lead time for this flash-flood event. The algorithmic system did not show as much skill in comparison with the dynamic model in providing precipitation forcing to the hydrologic model. The discharge forecasts based on the dynamic-model and algorithmic-system inputs point to the need to improve the ability to forecast convective storms, especially if models such as these eventually are to be used in operational flood forecasting.

  9. Near Real Time Integration of Satellite and Radar Data for Probabilistic Nearcasting of Severe Weather

    NASA Astrophysics Data System (ADS)

    Pavolonis, M. J.; Cintineo, J.; Sieglaff, J.; Lindsey, D. T.

    2014-12-01

    The formation, maintenance, and severity of thunderstorms that produce large hail, strong winds, and tornadoes are often difficult to forecast due to their rapid evolution and complex interactions with environmental features that are challenging to directly observe. This paper describes an empirical, data driven, approach to forecasting severe convection through fusion of near real time data from several sources. More specifically, data from the Geostationary Operational Environmental Satellites (GOES), the Next Generation Weather Radar (NEXRAD) network, and the Rapid Refresh (RAP) numerical weather prediction (NWP) model are used to drive a naïve Bayesian classifier. Each observation source provides unique information during different periods of storm development (i.e., the pre-storm environment, storm initiation and growth, and hydrometeor intensification). The model is designed to provide warning guidance to forecasters in the near-term (0-60 min), by quantifying several key temporal and spatial attributes of developing convection. The probabilistic model, known as ProbSevere, has been running in near real time at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS) since April of 2013 and was formally evaluated by National Weather Service (NWS) forecasters at the Hazardous Weather Testbed (HWT) in the spring of 2014. Validation studies and forecaster feedback indicated that the ProbSevere model, which is driven by near real time data, could be used to improve severe weather warning operations. In this paper, we will give an overview of the ProbSevere model, including performance statistics, and describe how the model will benefit from the next generation of GOES satellites (GOES-R).

  10. Assimilating Doppler radar radial velocity and reflectivity observations in the weather research and forecasting model by a proper orthogonal-decomposition-based ensemble, three-dimensional variational assimilation method

    NASA Astrophysics Data System (ADS)

    Pan, Xiaoduo; Tian, Xiangjun; Li, Xin; Xie, Zhenghui; Shao, Aimei; Lu, Chunyan

    2012-09-01

    Doppler radar observations with high spatial and temporal resolution can effectively improve the description of small-scale structures in the initial condition and enhance the mesoscale and microscale model skills of numerical weather prediction (NWP). In this paper, Doppler radar radial velocity and reflectivity are simultaneously assimilated into a weather research and forecasting (WRF) model by a proper orthogonal-decomposition-based ensemble, three-dimensional variational assimilation method (referred to as PODEn3DVar), which therefore forms the PODEn3DVar-based radar assimilation system (referred to as WRF-PODEn3DVar). The main advantages of WRF-PODEn3DVar over the standard WRF-3DVar are that (1) the PODEn3DVar provides flow-dependent covariances through the evolving ensemble of short-range forecasts, and (2) the PODEn3DVar analysis can be obtained directly without an iterative process, which significantly simplifies the assimilation. Results from real data assimilation experiments with the WRF model show that WRF-PODEn3DVar simulation yields better rainfall forecasting than radar retrieval, and radar retrieval is better than the standard WRF-3DVar assimilation, probably because of the flow-dependence character embedded in the WRF-PODEn3DVar.

  11. Comparison of the Scaling Characteristics of Rainfall Derived from Space-based and Ground-based Radar Observations

    NASA Astrophysics Data System (ADS)

    Gebremichael, M.; Over, T. M.; Krajewski, W. F.

    2004-05-01

    The authors compare the scaling characteristics of tropical rainfall derived from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the S-band ground-based radar (GR). Compared with the PR, the GR has a lower minimum detectable signal (-108 dBm instead of 17 dBZ); a better horizontal resolution (the gate spacing is 250 m, instead of 4.3 km resolution at nadir); and a nonattenuating wavelength (~10 cm instead of 2.2 cm). The differences between the PR and GR radar characteristics and viewing geometries lead to important differences in sensitivity, attenuation, and resolution. Comparison of the scaling characteristics of rainfall derived from the GR and PR is helpful to identify the potential and limitation of the PR. In this work, the authors use the PR and GR data collected from three primary TRMM Ground Validation (GV) sites. This dataset includes 18 months of data from the Houston, Texas, site; 30 months from the Melbourne, Florida, GV site; and 11 months from the Kwajalein Atoll, Republic of Marshall Islands, GV site. The GR data used in this study are the current 2A-53 products prepared by the NASA TRMM Office. Under the assumption of scaling invariance, the authors perform a detailed comparison of the scaling properties of rainfall derived from the PR and GR rainfall products for the three sites. Results using the scaling of moments function show that (1) both products reveal that the scaling parameter, which characterizes the scaling of rainy regions, can be related to the large-scale spatial average rain rate by a one-to-one function, and the function parameters obtained from the PR and GR are remarkably similar; (2) the values of the scaling parameter, which characterizes the curvature of the scaling function, obtained from the PR are consistently lower than those obtained from the GR; and (3) the differences between the PR- and GR-derived scaling characteristics are attributed to the differences in the sensor characteristics, as the temporal sampling of the TRMM PR is shown to adequately capture the scaling properties of rainfall. The authors also investigate the assumption of scaling invariance using a simulation-based approach. Results show that more than 25% of the rain events do not exhibit scaling invariance in moment orders of 0 and 2. The behavior of the deviation from the scaling and its implication on the type of modeling cascade are discussed.

  12. Application of the Hess-Brezowsky classification to the identification of weather patterns causing heavy winter rainfall in Brittany (France)

    NASA Astrophysics Data System (ADS)

    Planchon, O.; Quénol, H.; Dupont, N.; Corgne, S.

    2009-07-01

    An accurate knowledge of the weather patterns causing winter rainfall over the Scorff watershed in western Brittany (W. France) was developed prior to studies of the impact of the climate factor on land use management, and of the hydrological reponses to rain-producing weather patterns. These two studies are carried out in the context of the climate change. The identification of rainy air-circulation types was realized using the objective computational version of the 29-type Hess and Brezowsky Grosswetterlagen system of classifying European synoptic regimes, for the cold season (November-March) of the 1958-2005 period at the reference weather station of Lorient, and 13 other stations located in western and southern Brittany, including a more detailed study for the wet 2000-2001 cold season for three reference stations of the Scorff watershed (Lorient, Plouay and Plouray). The precipitation proportion (including the days with rainfall ≥20 mm) was calculated by major air-circulation type (GWT: see Appendix A) and by individual air-circulation subtype (GWL: see Appendix A) for the studied time-period. The most frequently occurrence of rainy days associated with westerly and southerly GWL confirmed well-known observations in western Europe and so justify the use of the Hess-Brezowsky classification in other areas outside Central Europe. The southern or south-western exposure of the watershed with a hilly inland area enhanced the heavy rainfall generated by the SW and S circulation types, and increased the difference between the rainfall amounts of coastal and inland stations during the wettest days.

  13. A Gaussian Random Field Approach for Merging Radar and Ground-Based Rainfall Data on Small Spatial and Temporal Scales

    NASA Astrophysics Data System (ADS)

    Krebsbach, K.; Friederichs, P.

    2014-12-01

    The generation of reliable precipitation products that explicitly account for spatial and temporal structures of precipitation events requires a combination of data with a variety of error structures and temporal resolutions. In-situ measurements are relatively accurate, but available only at sparse and irregularly distributed locations, whereas remote measurements cover areas but suffer from spatially and temporally inhomogeneous systematic errors. Besides gauge measurements are available on coarser spatial and temporal resolution in contrast to remote sensing measurements which are given on a fine spatial and temporal resolution. In our study we use precipitation rates from the composit of two X-band radars in Bonn and Jülich in Germany. Our aim is to formulate a statistical space-time model that aggregates and disaggregates precipitation rates from radar and gauge observations. We model a Gaussian random field as underlying process, where we face the task of dealing with a large non-Gaussian data set. To start the analysis of the unadjusted radar rainfall rates, we follow the work of D. Allcroft and C. Glasbey (2003) and transform the data to a truncated Gaussian distribution. The advantage of the latent variable approach is that it takes account of the occurence of rainfall and the intensity using a single process. We proceed by estimating the empirical correlation from these transformed values with maximum likelihood methods and fit a parametric correlation function that gives rise to a Gaussian random field. Since the transformation gives censored values to dry locations, we simulate values for this area that lie below some threshold and extend the Gaussian field to the whole domain. In order to merge gauge and radar data for precipitation, we first aggregate the data to a scale on which the comparison is reasonable and then disaggregate again back to smaller desirable scales. The disaggregation step consists of calculating the difference between radar aggregate and small scale measurements and the difference between gauge aggregate and derived small scale measurements. Then the spatial structure of the radar anomalies is used to simulate the gauge anomalies on the whole field. In the end we add the simulation to a combined estimator of the radar and gauge aggregates and obtain the small scale merging product.

  14. Visualization and Nowcasting for Aviation using online verified ensemble weather radar extrapolation.

    NASA Astrophysics Data System (ADS)

    Kaltenboeck, Rudolf; Kerschbaum, Markus; Hennermann, Karin; Mayer, Stefan

    2013-04-01

    Nowcasting of precipitation events, especially thunderstorm events or winter storms, has high impact on flight safety and efficiency for air traffic management. Future strategic planning by air traffic control will result in circumnavigation of potential hazardous areas, reduction of load around efficiency hot spots by offering alternatives, increase of handling capacity, anticipation of avoidance manoeuvres and increase of awareness before dangerous areas are entered by aircraft. To facilitate this rapid update forecasts of location, intensity, size, movement and development of local storms are necessary. Weather radar data deliver precipitation analysis of high temporal and spatial resolution close to real time by using clever scanning strategies. These data are the basis to generate rapid update forecasts in a time frame up to 2 hours and more for applications in aviation meteorological service provision, such as optimizing safety and economic impact in the context of sub-scale phenomena. On the basis of tracking radar echoes by correlation the movement vectors of successive weather radar images are calculated. For every new successive radar image a set of ensemble precipitation fields is collected by using different parameter sets like pattern match size, different time steps, filter methods and an implementation of history of tracking vectors and plausibility checks. This method considers the uncertainty in rain field displacement and different scales in time and space. By validating manually a set of case studies, the best verification method and skill score is defined and implemented into an online-verification scheme which calculates the optimized forecasts for different time steps and different areas by using different extrapolation ensemble members. To get information about the quality and reliability of the extrapolation process additional information of data quality (e.g. shielding in Alpine areas) is extrapolated and combined with an extrapolation-quality-index. Subsequently the probability and quality information of the forecast ensemble is available and flexible blending to numerical prediction model for each subarea is possible. Simultaneously with automatic processing the ensemble nowcasting product is visualized in a new innovative way which combines the intensity, probability and quality information for different subareas in one forecast image.

  15. The evaluation of satellite-borne weather radar system designs using real ground-based radar data

    NASA Technical Reports Server (NTRS)

    Dobson, E. B.; Kalshoven, J. E., Jr.

    1977-01-01

    The paper presents method of evaluating proposed satellite radar systems using real radar data, and discusses methods of displaying the results which will hopefully facilitate easy comparison of systems. A single pencil beam pulsed radar system is considered while the precipitation data base comes from six rain days observed by SPANDAR. The many additional factors that must be considered in the radar equation such as attenuation and scattering (Mie and Rayleigh) are discussed along with some indication where possible errors lie.

  16. Hands-On Learning Modules for Interdisciplinary Environments: An Example with a Focus on Weather Radar Applications

    ERIC Educational Resources Information Center

    Chilson, P. B.; Yeary, M. B.

    2012-01-01

    Learning modules provide an effective means of encouraging cognition and active learning. This paper discusses several such modules that have been developed within a course on weather radar applications intended for students from Electrical Engineering and Meteorology. The modules were designed both to promote interdisciplinary exchange between…

  17. Hands-On Learning Modules for Interdisciplinary Environments: An Example with a Focus on Weather Radar Applications

    ERIC Educational Resources Information Center

    Chilson, P. B.; Yeary, M. B.

    2012-01-01

    Learning modules provide an effective means of encouraging cognition and active learning. This paper discusses several such modules that have been developed within a course on weather radar applications intended for students from Electrical Engineering and Meteorology. The modules were designed both to promote interdisciplinary exchange between

  18. The New Weather Radar for America's Space Program in Florida: A Temperature Profile Adaptive Scan Strategy

    NASA Technical Reports Server (NTRS)

    Carey, L. D.; Petersen, W. A.; Deierling, W.; Roeder, W. P.

    2009-01-01

    A new weather radar is being acquired for use in support of America s space program at Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick AFB on the east coast of central Florida. This new radar replaces the modified WSR-74C at Patrick AFB that has been in use since 1984. The new radar is a Radtec TDR 43-250, which has Doppler and dual polarization capability. A new fixed scan strategy was designed to best support the space program. The fixed scan strategy represents a complex compromise between many competing factors and relies on climatological heights of various temperatures that are important for improved lightning forecasting and evaluation of Lightning Launch Commit Criteria (LCC), which are the weather rules to avoid lightning strikes to in-flight rockets. The 0 C to -20 C layer is vital since most generation of electric charge occurs within it and so it is critical in evaluating Lightning LCC and in forecasting lightning. These are two of the most important duties of 45 WS. While the fixed scan strategy that covers most of the climatological variation of the 0 C to -20 C levels with high resolution ensures that these critical temperatures are well covered most of the time, it also means that on any particular day the radar is spending precious time scanning at angles covering less important heights. The goal of this project is to develop a user-friendly, Interactive Data Language (IDL) computer program that will automatically generate optimized radar scan strategies that adapt to user input of the temperature profile and other important parameters. By using only the required scan angles output by the temperature profile adaptive scan strategy program, faster update times for volume scans and/or collection of more samples per gate for better data quality is possible, while maintaining high resolution at the critical temperature levels. The temperature profile adaptive technique will also take into account earth curvature and refraction when geo-locating the radar beam (i.e., beam height and arc distance), including non-standard refraction based on the user-input temperature profile. In addition to temperature profile adaptivity, this paper will also summarize the other requirements for this scan strategy program such as detection of low-level boundaries, detection of anvil clouds, reducing the Cone Of Silence, and allowing for times when deep convective clouds will not occur. The adaptive technique will be carefully compared to and benchmarked against the new fixed scan strategy. Specific environmental scenarios in which the adaptive scan strategy is able to optimize and improve coverage and resolution at critical heights, scan time, and/or sample numbers relative to the fixed scan strategy will be presented.

  19. Assessment of bird response to the Migratory Bird Habitat Initiative using weather-surveillance radar

    USGS Publications Warehouse

    Sieges, Mason L.; Smolinsky, Jaclyn A.; Baldwin, Michael J.; Barrow, Wylie C.; Randall, Lori A.; Buler, Jeffrey J.

    2014-01-01

    In response to the Deepwater Horizon oil spill in spring 2010, the Natural Resources Conservation Service implemented the Migratory Bird Habitat Initiative (MBHI) to provide temporary wetland habitat for migrating and wintering waterfowl, shorebirds, and other birds along the northern Gulf of Mexico via managed flooding of agricultural lands. We used weather-surveillance radar to conduct broad regional assessments of bird response to MBHI activities within the Mississippi Alluvial Valley and the West Gulf Coastal Plain. Across both regions, birds responded positively to MBHI management by exhibiting greater relative bird densities within sites relative to pre-management conditions in prior years and relative to surrounding non-flooded agricultural lands. Bird density at MBHI sites was generally greatest during winter for both regions. Unusually high flooding in the years prior to implementation of the MBHI confounded detection of overall changes in remotely sensed soil wetness across sites. The magnitude of bird response at MBHI sites compared to prior years and to non-flooded agricultural lands was generally related to the surrounding landscape context: proximity to areas of high bird density, amount of forested wetlands, emergent marsh, non-flooded agriculture, or permanent open water. However, these relationships varied in strength and direction between regions and seasons, a finding which we attribute to differences in seasonal bird composition and broad regional differences in landscape configuration and composition. We detected greater increases in relative bird use at sites in closer proximity to areas of high bird density during winter in both regions. Additionally, bird density was greater during winter at sites with more emergent marsh in the surrounding landscape. Thus, bird use of managed wetlands could be maximized by enrolling lands located near areas of known bird concentration and within a mosaic of existing wetlands. Weather-radar observations provide strong evidence that MBHI sites located inland from coastal wetlands impacted by the oil spill provided wetland habitat used by a variety of birds.

  20. Comparison of imaging laser radars based on range gating under different weather conditions

    NASA Astrophysics Data System (ADS)

    von der Fecht, Arno; Rothe, Hendrik

    1998-09-01

    This paper discusses the development and the experimental results of two imaging laser radar systems based on range gating. We designed an 128 X 128 pixel laser radar working at the eye-safe wavelength of 1574 nm without a scanner. The laser is a Q-switched, flashlamp pumped, Nd:YAG laser with Optical Parametric Oscillator. It achieves 60 mJ output energy at the video range of 25 Hz. As detector we use a high sensitive (68% quantum efficiency) InGaAs camera with a special designed Electro-Optical Modulator objective providing 18 ns gating time. The first laser illuminated images will be presented. The second system is working at the wavelength of 532 nm and uses a gated viewing camera including a Multi Channel Plate II generation with a maximum gain of 18000. We examined the system performance under different weather conditions especially at a range between 500 m and 1500 m. For both systems the field of view is fixed at 12 mrad, that means we illuminate a 12 X 12 m field at 1 km range. The outdoor experiments were taken over a period of 2 weeks, where we had on the one hand sun and on the other hand light and moderate rain with a rainrate up to 10 mm/h and a visibility of 490 m.

  1. Synoptic weather patterns associated with intense ENSO rainfall in the southwest United States

    NASA Astrophysics Data System (ADS)

    Feldl, N.; Roe, G. H.

    2010-12-01

    La Niña winters exhibit significant local enhancement of heavy rainfall in the southwest United States, relative to El Niño. This contrasts with average daily rainfall intensity, which is instead increased during El Niño winters. The present study explores the relationship between heavy rainfall and associated atmospheric circulation patterns. Using composite analysis, we find that heavy rainfall events in the southwest arise from the presence of a persistent offshore trough and simultaneous emplacement of a strong source of subtropical water vapor. Greater intensity of these storms during La Niña is consistent with a deeper offshore trough leading to strengthened moisture fluxes. Composite circulation patterns survive amongst a large degree of synoptic variability, highlighting the importance of understanding this variability when making regional climate predictions.

  2. Rainfall estimates for hydrological models: Comparing rain gauge, radar and microwave link data as input for the Wageningen Lowland Runoff Simulator (WALRUS)

    NASA Astrophysics Data System (ADS)

    Brauer, Claudia; Overeem, Aart; Uijlenhoet, Remko

    2015-04-01

    Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of differences in rainfall estimates on discharge simulations in a lowland catchment by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in the Hupsel Brook catchment. We used two automatic rain gauges with hourly resolution, located inside the catchment (the base run) and 30 km northeast. Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. Traditionally, the precipitation research community places emphasis on quantifying spatial errors and uncertainty, but for hydrological applications, temporal errors and uncertainty should be quantified as well. Its memory makes the hydrologic system sensitive to missed or badly timed rainfall events, but also emphasizes the effect of a bias in rainfall estimates. Systematic underestimation of rainfall by the uncorrected operational radar product leads to very dry model states and an increasing underestimation of discharge. Using the rain gauge 30 km northeast of the catchment yields good results for climatological studies, but not for forecasting individual floods. Simulating discharge using the maps derived from microwave link data and the gauge-adjusted radar product yields good results for both events and climatological studies. This indicates that these products can be used in catchments without gauges in or near the catchment. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. Improving rainfall measurements can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.

  3. Rainfall observations by an airbourne dual-fequency precipitation radar during CAMEX-4

    NASA Technical Reports Server (NTRS)

    Im, E.; Durden, S. L.; Sadowy, G.; Li, L.

    2002-01-01

    The 2d Generation Precipitation Radar is a new design for a dual-frequency (13.4 and 35.6 GHz) spaceborne precipitation radar. An airborne PR-2 simulator has been developed to demonstrate key technologies. This airborne system was flown on the NASA DC-8 aircraft during the 4th Convection and Moisture Experiment in 2001. Data were acquired in Tropical Storms Chantal and Gabrielle, Hurricane Humberto, and in several more localized convective systems. The authors discuss the design of thePR-2 airborne radar and show observations from CAMEX-4. Overall, the observations validated the design of PR-2 and provide an extensive data set for scientific analysis.

  4. Three unconventional airborne radar clues to severe convective storms

    NASA Astrophysics Data System (ADS)

    Trammell, Archie

    1989-01-01

    Even the most experienced commercial aircraft pilots have been found either to not possess the radar-operating and -interpreting skills required to differentiate between ground and weather echoes, or to possess such skills but no confidence in the ability of airborne radar to warn them of hazardous convective storms. It is presently noted that a radar reflectivity greater than 50 dbz, which corresponds to a rainfall rate of more than 4 inches/hr, will likely present the pilot with problems reflected in convective weather accident statistics; 9 out of 10 such accidents have occurred at rainfall rates approaching or exceeding 4 inches/hr.

  5. Lithological and textural controls on radar and diurnal thermal signatures of weathered volcanic deposits, Lunar Crater region, Nevada

    NASA Technical Reports Server (NTRS)

    Plaut, Jeffrey J.; Rivard, Benoit

    1992-01-01

    Radar backscatter intensity as measured by calibrated synthetic aperture radar (SAR) systems is primarily controlled by three factors: local incidence angle, wavelength-scale roughness, and dielectric permittivity of surface materials. Radar observations may be of limited use for geological investigations of surface composition, unless the relationships between lithology and the above characteristics can be adequately understood. In arid terrains, such as the Southwest U.S., weathering signatures (e.g. soil development, fracturing, debris grain size and shape, and hill slope characteristics) are controlled to some extent by lithologic characteristics of the parent bedrock. These textural features of outcrops and their associated debris will affect radar backscatter to varying degrees, and the multiple-wavelength capability of the JPL Airborne SAR (AIRSAR) system allows sampling of textures at three distinct scales. Diurnal temperature excursions of geologic surfaces are controlled primarily by the thermal inertia of surface materials, which is a measure of the resistance of a material to a change in temperature. Other influences include albedo, surface slopes affecting insolation, local meteorological conditions and surface emissivity at the relevant thermal wavelengths. To first order, thermal inertia variations on arid terrain surfaces result from grain size distribution and porosity differences, at scales ranging from micrometers to tens of meters. Diurnal thermal emission observations, such as those made by the JPL Thermal Infrared Multispectral Scanner (TIMS) airborne instrument, are thus influenced by geometric surface characteristics at scales comparable to those controlling radar backscatter. A preliminary report on a project involving a combination of field, laboratory and remote sensing observations of weathered felsic-to basaltic volcanic rock units exposed in the southern part of the Lunar Crater Volcanic Field, in the Pancake Range of central Nevada is presented. Focus is on the relationship of radar backscatter cross sections at multiple wavelengths, apparent diurnal temperature excursions identified in multi-temporal TIMS images, surface geometries related to weathering style, and parent bedrock lithology.

  6. Tropical convective systems life cycle characteristics from geostationary satellite and precipitating estimates derived from TRMM and ground weather radar observations for the West African and South American regions

    NASA Astrophysics Data System (ADS)

    Fiolleau, T.; Roca, R.; Angelis, F. C.; Viltard, N.

    2012-12-01

    In the tropics most of the rainfall comes in the form of individual storm events embedded in the synoptic circulations (e.g., monsoons). Understanding the rainfall and its variability hence requires to document these highly contributing tropical convective systems (MCS). Our knowledge of the MCS life cycle, from a physical point of view mainly arises from individual observational campaigns heavily based on ground radar observations. While this large part of observations enabled the creation of conceptual models of MCS life cycle, it nevertheless does not reach any statistically significant integrated perspective yet. To overcome this limitation, a composite technique, that will serve as a Day-1 algorithm for the Megha-Tropiques mission, is considered in this study. this method is based on a collocation in space and time of the level-2 rainfall estimates (BRAIN) derived from the TMI radiometer onboard TRMM with the cloud systems identified by a new MCS tracking algorithm called TOOCAN and based on a 3-dimensional segmentation (image + time) of the geostationary IR imagery. To complete this study, a similar method is also developed collocating the cloud systems with the precipitating features derived from the ground weather radar which has been deployed during the CHUVA campaign over several Brazilian regions from 2010 up to now. A comparison of the MCSs life cycle is then performed for the 2010-2012 summer seasons over the West African, and South American regions. On the whole region of study, the results show that the temporal evolution of the cold cloud shield associated to MCSs describes a symmetry between the growth and the decay phases. It is also shown that the parameters of the conceptual model of MCSs are strongly correlated, reducing thereby the problem to a single degree of freedom. At the system scale, over both land and oceanic regions, rainfall is described by an increase at the beginning (the first third) of the life cycle and then smoothly decreases as the system shrinks and dissipates. The evolutions of the precipitating properties associated to MCSs indicate that the life cycle of these systems can be described by three phases: initiation, mature and dissipation. This pattern is robust across the entire monsoonal region and the scale factors of this idealized model indicate complex regional specificities.

  7. Ground-based microwave weather radar observations and retrievals during the 2014 Holuhraun eruption (Bárðarbunga, Iceland)

    NASA Astrophysics Data System (ADS)

    Mereu, Luigi; Silvio Marzano, Frank; Barsotti, Sara; Montopoli, Mario; Yeo, Richard; Arngrimsson, Hermann; Björnsson, Halldór; Bonadonna, Costanza

    2015-04-01

    During an eruptive event the real-time forecasting of ash dispersal into the atmosphere is a key factor to prevent air traffic disasters. The ash plume is extremely hazardous to aircraft that inadvertently may fly through it. Real-time monitoring of such phenomena is crucial, particularly to obtain specific data for the initialization of eruption and dispersion models in terms of source parameters. The latter, such as plume height, ash concentration, mass flow rate and size spectra, are usually very difficult to measure or to estimate with a relatively good accuracy. Over the last years different techniques have been developed to improved ash plume detection and retrieval. Satellite-based observations, using multi-frequency visible and infrared radiometers, are usually exploited for monitoring and measuring dispersed ash clouds. The observations from geostationary orbit suffer from a relatively poor spatial resolution, whereas the low orbit level has a relatively poor temporal resolution. Moreover, the field-of-view of infrared radiometric measurements may be reduced by obstructions caused by water and ice clouds lying between the ground and the sensor's antenna. Weather radar-based observations represent an emerging technique to detect and, to a certain extent, mitigate the hazard from the ash plumes. Ground-based microwave scanning radar systems can provide the three-dimensional information about the detected ash volume with a fairly high spatial resolution every few minutes and in all weather conditions. Methodological studies have recently investigated the possibility of using single-polarization and dual-polarization ground-based radar for the remote sensing of volcanic ash cloud. In this respect, radar observations can be complementary to satellite observations. A microphysical electromagnetic characterization of volcanic ash was carried out in terms of dielectric properties, composition, size and orientation of ash particles. An extended Volcanic Ash Radar Retrieval (VARR) algorithm for single-polarization and double-polarization systems, shown in previous work, has been applied to C-band and X-band weather radar data. In this work we show radar based estimations of eruptive source parameters for Holuhraun events in the fall of 2014. This extremely gas-rich eruption was characterized by sustained lava fountaining in the first months. At the same time some ash-rich episodes were reported from the field together with minor tephra fallout occurring close to the eruption site. Since the beginning of the eruption, the Icelandic Meteorological Office (IMO) monitored the volcanic plume using two ground-based radars: a C-band weather radar (5.5 GHz) in Egilsstaðir and an X-band polarimetric mobile radar (9.4 GHz) located at Vaðalda, about 20 km away from the eruption site. The VARR algorithm has been applied to few specific events and the radar products, such as top plume height, concentration, ash load and mass flow rate, derived from the two radars, are here discussed in terms of retrievals and inter-comparisons with available in-situ information. Both radar-based estimations show a presence of volcanic particles in the observed plume. Also, airborne fine ash particles are identified at low levels of plume probably due to a wind-induced re-suspension of dust and ancient volcanic ash deposited in the area around Holuhraun.

  8. Spatial patterns in thunderstorm rainfall events and their coupling with watershed hydrological response 1907

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Weather radar systems provide detailed information on spatial rainfall patterns known to play a significant role in runoff generation processes. In the current study, we present an innovative approach to exploit spatial rainfall information of air mass thunderstorms and link it with a watershed hydr...

  9. Spatial patterns in thunderstorm rainfall events and their coupling with watershed hydrological response 1894

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Weather radar systems provide detailed information on spatial rainfall patterns known to play a significant role in runoff generation processes. In the current study, we present an innovative approach to exploit spatial rainfall of air mass thunderstorms and link it with a watershed hydrological mo...

  10. Application of wind-profiling radar data to the analysis of dust weather in the Taklimakan Desert.

    PubMed

    Wang, Minzhong; Wei, Wenshou; Ruan, Zheng; He, Qing; Ge, Runsheng

    2013-06-01

    The Urumqi Institute of Desert Meteorology of the China Meteorological Administration carried out an atmospheric scientific experiment to detect dust weather using a wind-profiling radar in the hinterland of the Taklimakan Desert in April 2010. Based on the wind-profiling data obtained from this experiment, this paper seeks to (a) analyze the characteristics of the horizontal wind field and vertical velocity of a breaking dust weather in a desert hinterland; (b) calculate and give the radar echo intensity and vertical distribution of a dust storm, blowing sand, and floating dust weather; and (c) discuss the atmosphere dust counts/concentration derived from the wind-profiling radar data. Studies show that: (a) A wind-profiling radar is an upper-air atmospheric remote sensing system that effectively detects and monitors dust. It captures the beginning and ending of a dust weather process as well as monitors the sand and dust being transported in the air in terms of height, thickness, and vertical intensity. (b) The echo intensity of a blowing sand and dust storm weather episode in Taklimakan is about -1~10 dBZ while that of floating dust -1~-15 dBZ, indicating that the dust echo intensity is significantly weaker than that of precipitation but stronger than that of clear air. (c) The vertical shear of horizontal wind and the maintenance of low-level east wind are usually dynamic factors causing a dust weather process in Taklimakan. The moment that the low-level horizontal wind field finds a shear over time, it often coincides with the onset of a sand blowing and dust storm weather process. (d) When a blowing sand or dust storm weather event occurs, the atmospheric vertical velocity tends to be of upward motion. This vertical upward movement of the atmosphere supported with a fast horizontal wind and a dry underlying surface carries dust particles from the ground up to the air to form blown sand or a dust storm. PMID:23099859

  11. The design and development of signal-processing algorithms for an airborne x-band Doppler weather radar

    NASA Technical Reports Server (NTRS)

    Nicholson, Shaun R.

    1994-01-01

    Improved measurements of precipitation will aid our understanding of the role of latent heating on global circulations. Spaceborne meteorological sensors such as the planned precipitation radar and microwave radiometers on the Tropical Rainfall Measurement Mission (TRMM) provide for the first time a comprehensive means of making these global measurements. Pre-TRMM activities include development of precipitation algorithms using existing satellite data, computer simulations, and measurements from limited aircraft campaigns. Since the TRMM radar will be the first spaceborne precipitation radar, there is limited experience with such measurements, and only recently have airborne radars become available that can attempt to address the issue of the limitations of a spaceborne radar. There are many questions regarding how much attenuation occurs in various cloud types and the effect of cloud vertical motions on the estimation of precipitation rates. The EDOP program being developed by NASA GSFC will provide data useful for testing both rain-retrieval algorithms and the importance of vertical motions on the rain measurements. The purpose of this report is to describe the design and development of real-time embedded parallel algorithms used by EDOP to extract reflectivity and Doppler products (velocity, spectrum width, and signal-to-noise ratio) as the first step in the aforementioned goals.

  12. Terminal Doppler Weather Radar Observation of Atmospheric Flow over Complex Terrain during Tropical Cyclone Passages.

    NASA Astrophysics Data System (ADS)

    Shun, C. M.; Lau, S. Y.; Lee, O. S. M.

    2003-12-01

    A Terminal Doppler Weather Radar (TDWR) started operation in Hong Kong, China, in 1997 for monitoring wind shear associated with thunderstorms affecting the Hong Kong International Airport. The airport was built on land reclaimed from the sea and lies to the immediate north of the mountainous Lantau Island, which has hills rising to nearly 1000 m. Since 1997, the airport experienced a number of tropical cyclone passages, some bringing strong southerly winds across these hills. Under these conditions the TDWR captured interesting but complex flow patterns in the lower atmosphere. The TDWR Doppler velocity datasets reveal features not previously observed with conventional instruments. These include shear lines, reverse flow, small-scale vortices, streaks of low-speed flow set against a high-speed background, as well as gap-related downslope high-speed flow. Hovmöller diagrams constructed from the Doppler velocity data bring out in considerable detail periodic shedding of vortices and transient wind patterns in the wake of the hills.

  13. Spaceborne radar measurements of verticle rainfall velocity: the non-uniform beam filling considerations

    NASA Technical Reports Server (NTRS)

    Im, E.; Tanelli, S.; Durden, S. L.; Facheris, L.; Giuli, D.; Smith, E. A.; Haddad, Z. S.

    2001-01-01

    In this paper, the characteristics of the Doppler power spectrum observed by a spaceborne precipitation radar, under on Uniform Beam Filling (NUBF) condion will be presented, and the expected performance of some standard Doppler estimators and that of a new inversion technique will be investigated and compared.

  14. Study on multifractal modeling of rainfall

    NASA Astrophysics Data System (ADS)

    Volpi, Elena; Lombardo, Federico; Russo, Fabio; Napolitano, Francesco; Baldini, Luca

    2010-05-01

    The identification of the spatial structure of rainfall is widely recognized as a key issue in the hydrological applications. An approach to this problem is based on the empirical detection of some regularities in hydrological observations, such as the scale-invariance properties of rainfall (e.g. [1]). Scaling properties can provide simple relationships to link the statistical distribution of the rainfall process at different spatial and temporal scales, in the ranges of which the power-law assumption can be verified [2]. However, it is very difficult if not impossible to be able to properly capture the high spatial variability of rainfall fields with traditional rain gauge networks, while modern weather radars are, potentially, an instrument capable of meeting this need because of the fine spatial resolution of radar data. This work focuses on the analysis of the scaling properties of rainfall in space by using data from a high density rain gauge network and from a weather radar both covering the urban area of Rome. The aim of the study is the identification of spatial scaling regimes, their ranges of validity, and the evaluation of the corresponding scaling properties. REFERENCES [1] Lovejoy, S. and Schertzer, D. Generalized scale invariance in the atmosphere and fractal models of rain. Water Resour. Res., 21(8), 1233-1250, 1985. [2] Marani, M. Non-power-law-scale properties of rainfall in space and time, Water Resour. Res., 41, W08413, doi:10.1029/2004WR003822, 2005.

  15. Field-Testing the Suitability of Microrain Radars to Describe the Spatial Gradients of the Vertical Structure of Rainfall in Mountainous Regions

    NASA Astrophysics Data System (ADS)

    Prat, O. P.; Barros, A. P.

    2009-04-01

    A Micro Rain Radar (MRR) was deployed twice in July/August and October/November 2008 for a total duration of three months at the top of a mountain ridge in the Great Smoky Mountains National Park in the Southern Appalachians. For the second period of observation, a second MRR was deployed at a lower altitude in a nearby valley. Observations from rain gauges and the MRR were used along with a microphysical model to simulate the rainfall events observed during the radar deployment. Results from an integrated analysis of the observations are presented here, with emphasis on characterizing the diurnal cycle of rainfall and ridge-valley gradients in vertical structure of rainfall with an emphasis on microphysical properties.

  16. Weather.

    ERIC Educational Resources Information Center

    Ruth, Amy, Ed.

    1996-01-01

    This theme issue of "The Goldfinch" focuses on weather in Iowa and weather lore. The bulletin contains historical articles, fiction, activities, and maps. The table of contents lists: (1) "Wild Rosie's Map"; (2) "History Mystery"; (3) "Iowa's Weather History"; (4) "Weather Wonders"; (6) "Seasonal Jobs"; (7) "Fiction: Winter Courage"; (8) "Stayin'…

  17. Experimental tests of methods for the measurement of rainfall rate using an airborne dual-wavelength radar

    NASA Technical Reports Server (NTRS)

    Meneghini, R.; Nakamura, K.; Ulbrich, C. W.; Atlas, D.

    1989-01-01

    Several attenuation-based methods for estimating the rainfall rate were applied to measurements made by an airborne dual-wavelength radar operating at 0.87 cm, the K(a)-band, and at 3 cm, the X-band. These methods included the traditional Z-R methods, designated Z(X)-R and Z(K)-R for the X- and K(a) band wavelengths, respectively; single- and dual-wavelength surface reference techniques (SRT and DSRT, respectively); and standard dual-wavelength methods with and without range-averaging. As the primary sources of error for these methods are nearly independent, agreement among the rain rates obtained with these methods would lend confidence in the results. Correlation coefficients obtained between the rainfall rates with the Z(X)-R and DSRT methods were generally between 0.7 and 0.9. Good agreement among the methods occurred most often in stratiform rain for rain rates betwen a few mm/hr to about 15 mm/hr, i.e., where attenuation at the shorter wavelength is significant but not so severe as to result in a loss of signal.

  18. On the Characterization of Rainfall Associated with U.S. Landfalling North Atlantic Tropical Cyclones Based on Satellite Data and Numerical Weather Prediction Outputs

    NASA Astrophysics Data System (ADS)

    Luitel, B. N.; Villarini, G.; Vecchi, G. A.

    2014-12-01

    When we talk about tropical cyclones (TCs), the first things that come to mind are strong winds and storm surge affecting the coastal areas. However, according to the Federal Emergency Management Agency (FEMA) 59% of the deaths caused by TCs since 1970 is due to fresh water flooding. Heavy rainfall associated with TCs accounts for 13% of heavy rainfall events nationwide for the June-October months, with this percentage being much higher if the focus is on the eastern and southern United States. This study focuses on the evaluation of precipitation associated with the North Atlantic TCs that affected the continental United States over the period 2007 - 2012. We evaluate the rainfall associated with these TCs using four satellite based rainfall products: Tropical Rainfall Measuring Mission - Multi-satellite Precipitation Analysis (TMPA; both real-time and research version); Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN); Climate Prediction Center (CPC) MORPHing technique (CMORPH). As a reference data we use gridded rainfall provided by CPC (Daily US Unified Gauge-Based Analysis of Precipitation). Rainfall fields from each of these satellite products are compared to the reference data, providing valuable information about the realism of these products in reproducing the rainfall associated with TCs affecting the continental United States. In addition to the satellite products, we evaluate the forecasted rainfall produced by five state-of-the-art numerical weather prediction (NWP) models: European Centre for Medium-Range Weather Forecasts (ECMWF), UK Met Office (UKMO), National Centers for Environmental Prediction (NCEP), China Meteorological Administration (CMA), and Canadian Meteorological Center (CMC). The skill of these models in reproducing TC rainfall is quantified for different lead times, and discussed in light of the performance of the satellite products.

  19. Using the new dual-polarimetric capability of WSR-88D to eliminate anomalous propagation and wind turbine effects in radar-rainfall

    NASA Astrophysics Data System (ADS)

    Seo, Bong-Chul; Krajewski, Witold F.; Mishra, Kumar Vijay

    2015-02-01

    This study addresses the effect that the interaction between anomalous radar beam propagation (AP) and wind turbines that are located far from the radar has on radar-rainfall estimates. The interference of wind turbines in radar observations may lead to significant errors in rainfall estimates since wind turbines are often clustered to form wind farms. In this study, we propose a novel approach - based on the polarimetric capability recently added to the WSR-88D NEXRAD radars - that identifies and eliminates wind turbine clutter along with common ground clutter AP effects. Our primary objective is to devise a physically meaningful and fully automated dual-polarimetric method that effectively handles clutter features, which are hard to detect using single-channel reflectivity data alone. To address this issue, we explore the feasibility of using polarimetric variables such as differential reflectivity (ZDR), copolar correlation (RHO), and differential phase (PHIDP). Accordingly, we developed three new approaches using polarimetric variables, which are combined with the AP detection algorithm that uses a three-dimensional structure of reflectivity. We evaluate the new algorithms in terms of both eliminating non-meteorological radar returns and preserving returns from actual rain. The proposed algorithm, which uses RHO conditioned on horizontal reflectivity values while also accounting for the variation of ZDR or PHIDP, shows good performance for the presented cases.

  20. Flash flood prediction using an uncalibrated hydrological model and radar rainfall data in a Mediterranean watershed under changing hydrological conditions

    NASA Astrophysics Data System (ADS)

    Rozalis, Shahar; Morin, Efrat; Yair, Yoav; Price, Colin

    2010-11-01

    SummaryFlash floods cause some of the most severe natural disasters in Europe but Mediterranean areas are especially vulnerable. They can cause devastating damage to property, infrastructures and loss of human life. The complexity of flash flood generation processes and their dependency on different factors related to watershed properties and rainfall characteristics make flash flood prediction a difficult task. In this study, as part of the EU-FLASH project, we used an uncalibrated hydrological model to simulate flow events in a 27 km2 Mediterranean watershed in Israel to analyze and better understand the various factors influencing flows. The model is based on the well-known SCS curve number method for rainfall-runoff calculations and on the kinematic wave method for flow routing. Existing data available from maps, GIS and field studies were used to define model parameters, and no further calibration was conducted to obtain a better fit between computed and observed flow data. The model rainfall input was obtained from the high temporal and spatial resolution radar data adjusted to rain gauges. Twenty flow events that occurred within the study area over a 15 year period were analyzed. The model shows a generally good capability in predicting flash flood peak discharge in terms of their general level, classified as low, medium or high (all high level events were correctly predicted). It was found that the model mainly well predicts flash floods generated by intense, short-lived convective storm events while model performances for low and moderate flows generated by more widespread winter storms were quite poor. The degree of urban development was found to have a large impact on runoff amount and peak discharge, with higher sensitivity of moderate and low flow events relative to high flows. Flash flood generation was also found to be very sensitive to the temporal distribution of rain intensity within a specific storm event.

  1. Applying bias correction for merging rain gauge and radar data

    NASA Astrophysics Data System (ADS)

    Rabiei, E.; Haberlandt, U.

    2015-03-01

    Weather radar provides areal rainfall information with very high temporal and spatial resolution. Radar data has been implemented in several hydrological applications despite the fact that the data suffers from varying sources of error. Several studies have attempted to propose methods for solving these problems. Additionally, weather radar usually underestimates or overestimates the rainfall amount. In this study, a new method is proposed for correcting radar data by implementing the quantile mapping bias correction method. Then, the radar data is merged with observed rainfall by conditional merging and kriging with external drift interpolation techniques. The merging product is analysed regarding the sensitivity of the two investigated methods to the radar data quality. After implementing bias correction, not only did the quality of the radar data improve, but also the performance of the interpolation techniques using radar data as additional information. In general, conditional merging showed greater sensitivity to radar data quality, but performed better than all the other interpolation techniques when using bias corrected radar data. Furthermore, a seasonal variation of interpolation performances has in general been observed. A practical example of using radar data for disaggregating stations from daily to hourly temporal resolution is also proposed in this study.

  2. Tropical Rainfall Measuring Mission

    NASA Technical Reports Server (NTRS)

    1999-01-01

    Tropical rainfall affects the lives and economics of a majority of the Earth's population. Tropical rain systems, such as hurricanes, typhoons, and monsoons, are crucial to sustaining the livelihoods of those living in the tropics. Excess rainfall can cause floods and great property and crop damage, whereas too little rainfall can cause drought and crop failure. The latent heat release during the process of precipitation is a major source of energy that drives the atmospheric circulation. This latent heat can intensify weather systems, affecting weather thousands of kilometers away, thus making tropical rainfall an important indicator of atmospheric circulation and short-term climate change. Tropical forests and the underlying soils are major sources of many of the atmosphere's trace constituents. Together, the forests and the atmosphere act as a water-energy regulating system. Most of the rainfall is returned to the atmosphere through evaporation and transpiration, and the atmospheric trace constituents take part in the recycling process. Hence, the hydrological cycle provides a direct link between tropical rainfall and the global cycles of carbon, nitrogen, and sulfur, all important trace materials for the Earth's system. Because rainfall is such an important component in the interactions between the ocean, atmosphere, land, and the biosphere, accurate measurements of rainfall are crucial to understanding the workings of the Earth-atmosphere system. The large spatial and temporal variability of rainfall systems, however, poses a major challenge to estimating global rainfall. So far, there has been a lack of rain gauge networks, especially over the oceans, which points to satellite measurement as the only means by which global observation of rainfall can be made. The Tropical Rainfall Measuring Mission (TRMM), jointly sponsored by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan, provides visible, infrared, and microwave observations of tropical and subtropical rain systems.The satellite observations are complemented by ground radar and rain gauge measurements to validate satellite rain estimation techniques. Goddard Space Flight Center's involvement includes the observatory, four instruments, integration and testing of the observatory, data processing and distribution, and satellite operations. TRMM has a design lifetime of three years. Data generated from TRMM and archived at the GDAAC are useful not only for hydrologists, atmospheric scientists, and climatologists, but also for the health community studying infectious diseases, the ocean research community, and the agricultural community.

  3. Space-Time Characteristics of Rainfall Diurnal Variations

    NASA Technical Reports Server (NTRS)

    Yang, Song; Kummerow, Chris; Olson, Bill; Smith, Eric A.; Einaudi, Franco (Technical Monitor)

    2001-01-01

    The space-time features of rainfall diurnal variation of precipitation are systematically investigated by using the Tropical Rainfall Measuring Mission (TRMM) precipitation products retrieved from TRMM microwave imager (TMI), precipitation radar (PR) and TMI/PR combined algorithms. Results demonstrate that diurnal variability of precipitation is obvious over tropical regions. The dominant feature of rainfall diurnal cycle over, ocean is that there is consistent rainfall peak in early morning, while there is a consistent rainfall peak in mid-late afternoon over land. The seasonal variation on intensity of rainfall diurnal cycle is clearly evidenced. Horizontal distributions of rainfall diurnal variations indicate that there is a clearly early-morning peak with a secondary peak in the middle-late afternoon in ocean rainfall at latitudes dominated by large-scale convergence and deep convection. There is also an analogous early-morning peak in land rainfall along with a stronger afternoon peak forced by surface heating. Amplitude analysis shows that the patterns and its evolution of rainfall diurnal cycle are very close to rainfall distribution pattern and its evolution. These results indicate that rainfall diurnal variations are strongly associated with large-scale convective systems and climate weather systems. Phase studies clearly present the regional and seasonal features of rainfall diurnal activities. Further studies on convective and stratiform rainfall show different characteristics of diurnal cycles. Their spatial and temporal variations of convective and stratiform rainfall indicate that mechanisms for rainfall diurnal variations vary with time and space.

  4. Physically-based Flood Modeling Driven by Radar Rainfall in the Upper Guadalupe River Basin, Texas

    NASA Astrophysics Data System (ADS)

    Sharif, H. O.; Chintalapudi, S.; El Hassan, A.

    2011-12-01

    The upstream portion of the Guadalupe River Basin (Upper Guadalupe River Basin) is prone to frequent flooding due to its physiographic properties (thin soils, exposed bedrock, and sparse vegetation). The Upper Guadalupe River watershed above Comfort, Texas drains an area of 2,170 square kilometers. This watershed is located at the central part of the Texas Hill Country. This study presents hydrologic analysis of the June 2002, November-2004, and August-2007 flood events that occurred in Upper Guadalupe River Basin. The physically based, distributed-parameter Gridded Surface Subsurface Hydrologic Analysis (GSSHA) hydrologic model was used to simulate the above flooding events. The first event was used in model while the other two were used for validation. GSSHA model was driven by both rain gauge and Multi-sensor Precipitation Estimator (MPE) rainfall inputs. Differences in simulation results were compared in terms of the hydrographs at different locations in the basin as well as the spatial distribution of hydrologic processes. GSSHA simulations driven by MPE rainfall match very well the USGS observed hydrograph. GSSHA simulation driven by rain gauge rainfall for June-2002 storm event underestimated the peak flow.

  5. An X-band solid-state FM-CW weather radar

    NASA Astrophysics Data System (ADS)

    Ligthart, L. P.; Nieuwkerk, L. R.

    1990-12-01

    FM-CW radar has grown to a mature state owing to new breakthroughs in microwave and computer hardware. Applications of FM-CW radar so far have been mainly in the field of tropospheric research, meteorology and ship navigation. The paper describes a radar to be used for rain-rate determination and rain-cell contouring. The central themes are system fundamentals, system design and construction, and real-time processing of the radar. The new radar is purely solid state, with a CW power of 1 watt. Owing to the use of X-band frequencies, the radar waves need to be corrected for spatial expansion and for rain-induced attenuation along the radar path, using real-time processing. Results demonstrate the potential capability for suppressing coherent ground clutter as well as for detecting rain cells.

  6. Input uncertainty in catchment models: an evaluation of the suitability of multiplicative rainfall error models using high resolution raingauge and radar data

    NASA Astrophysics Data System (ADS)

    Jackson, Bethanna; McMillan, Hilary; Clark, Martyn; Kavetski, Dmitri; Woods, Ross

    2010-05-01

    This paper presents an investigation of rainfall error models used in rainfall-runoff model calibration and prediction. A growing number of studies now specify an error model for rainfall input, usually simple in form due to computational constraints during parameter estimation. Such rainfall error models have not typically been validated against experimental evidence. If the data uncertainty hypotheses and assumptions are unsupported, the interactions between input and structural model error may significantly contaminate the inference and lead to unreliable parameter estimates and model predictions. It is therefore important that the data error models should be developed using data analysis that is independent from the hydrological model calibration, to bring genuine independent information into the inference. In this study we use data from the 50 km2 Mahurangi catchment in Northland, New Zealand, where there is detailed space-time information on rainfall from both a dense tipping bucket raingauge network (13 stations) and X-band radar rainfall estimates. This high resolution data is used to provide insights on the suitability of the common multiplicative rainfall error model for use at varying spatial and temporal scales of hydrological models. We first present an analysis of the spatial variability and uncertainty in rainfall when considered solely as a binary (wet/dry) process. This type of analysis is a crucial check on the assumptions underlying multiplicative rainfall error models, since the latter cannot account for rain events with only partial catchment cover that are hence not recorded by a rain gauge. Secondly, we examine the consistency of rainfall quantities over the catchment; based both on complete rainfall records and also for individual storm events when correct estimation of rainfall is most crucial. This allows us to estimate the statistical distributions of rainfall multipliers and test if these could form the basis of an adequate rainfall error model and put multipliers into the context of events. Results highlight some important results for understanding rainfall uncertainty and deriving data-based probabilistic error models for use in hydrological calibration. In the Mahurangi catchment, multiplicative error appears to be a suitable formulation for correcting mean catchment rainfall values during high-rainfall periods (e.g. intensities over 1 mm/hour); or for longer timesteps at any rainfall intensity (timestep 1 day or greater). We suggest that the effect of timestep on multiplier suitability is regulated by catchment size: specifically the time required for typical raincells to cross the catchment could be used as a first estimate of critical timestep. The standard distribution used for rainfall multipliers, the lognormal, provided a relatively close fit to the empirical multiplier distributions. However the empirical distributions have greater excess kurtosis and positive skew than the lognormal. Since heavy rainfall events display multiplier distributions differing most significantly from the lognormal, a skewed and heavier-tailed distribution to be used for times of high rainfall would more faithfully reproduce the observed error characteristics. Lastly, the high resolution of the data available demonstrated the time/space complexity of rainfall behaviour that cannot be corrected by a simple multiplicative error on measured rainfall. A hydrological model that aims to capture the full effects of rainfall variability would need an additional mechanism, such as a distribution function approach to rainfall input; or a blurred threshold for processes such as infiltration excess.

  7. Intercomparison of snowfall estimates derived from the CloudSat Cloud Profiling Radar and the ground based weather radar network over Sweden

    NASA Astrophysics Data System (ADS)

    Norin, L.; Devasthale, A.; L'Ecuyer, T. S.; Wood, N. B.; Smalley, M.

    2015-08-01

    To be able to estimate snowfall accurately is important for both weather and climate applications. Ground-based weather radars and space-based satellite sensors are often used as viable alternatives to rain-gauges to estimate precipitation in this context. The Cloud Profiling Radar (CPR) onboard CloudSat is especially proving to be a useful tool to map snowfall globally, in part due to its high sensitivity to light precipitation and ability to provide near-global vertical structure. The importance of having snowfall estimates from CloudSat/CPR further increases in the high latitude regions as other ground-based observations become sparse and passive satellite sensors suffer from inherent limitations. Here we intercompared snowfall estimates from two observing systems, CloudSat and Swerad, the Swedish national weather radar network. Swerad offers one of the best calibrated data sets of precipitation amount at very high latitudes that are anchored to rain-gauges and that can be exploited to evaluate usefulness of CloudSat/CPR snowfall estimates in the polar regions. In total 7.2×105 matchups of CloudSat and Swerad over Sweden were inter-compared covering all but summer months (October to May) from 2008 to 2010. The intercomparison shows encouraging agreement between these two observing systems despite their different sensitivities and user applications. The best agreement is observed when CloudSat passes close to a Swerad station (46-82 km), when the observational conditions for both systems are comparable. Larger disagreements outside this range suggest that both platforms have difficulty with shallow snow but for different reasons. The correlation between Swerad and CloudSat degrades with increasing distance from the nearest Swerad station as Swerad's sensitivity decreases as a function of distance and Swerad also tends to overshoots low level precipitating systems further away from the station, leading to underestimation of snowfall rate and occasionally missing the precipitation altogether. Further investigations of various statistical metrics, such as the probability of detection, false alarm rate, hit rate, and the Hanssen-Kuipers skill scores, and the sensitivity of these metrics to snowfall rate and the distance from the radar station, were carried out. The results of these investigations highlight the strengths and the limitations of both observing systems at the lower and upper ends of snowfall distributions and the range of uncertainties that could be expected from these systems in the high latitude regions.

  8. Intercomparison of snowfall estimates derived from the CloudSat Cloud Profiling Radar and the ground-based weather radar network over Sweden

    NASA Astrophysics Data System (ADS)

    Norin, L.; Devasthale, A.; L'Ecuyer, T. S.; Wood, N. B.; Smalley, M.

    2015-12-01

    Accurate snowfall estimates are important for both weather and climate applications. Ground-based weather radars and space-based satellite sensors are often used as viable alternatives to rain gauges to estimate precipitation in this context. In particular, the Cloud Profiling Radar (CPR) on board CloudSat is proving to be a useful tool to map snowfall globally, in part due to its high sensitivity to light precipitation and its ability to provide near-global vertical structure. CloudSat snowfall estimates play a particularly important role in the high-latitude regions as other ground-based observations become sparse and passive satellite sensors suffer from inherent limitations. In this paper, snowfall estimates from two observing systems - Swerad, the Swedish national weather radar network, and CloudSat - are compared. Swerad offers a well-calibrated data set of precipitation rates with high spatial and temporal resolution, at very high latitudes. The measurements are anchored to rain gauges and provide valuable insights into the usefulness of CloudSat CPR's snowfall estimates in the polar regions. In total, 7.2 × 105 matchups of CloudSat and Swerad observations from 2008 through 2010 were intercompared, covering all but the summer months (June to September). The intercomparison shows encouraging agreement between the two observing systems despite their different sensitivities and user applications. The best agreement is observed when CloudSat passes close to a Swerad station (46-82 km), where the observational conditions for both systems are comparable. Larger disagreements outside this range suggest that both platforms have difficulty with shallow snow but for different reasons. The correlation between Swerad and CloudSat degrades with increasing distance from the nearest Swerad station, as Swerad's sensitivity decreases as a function of distance. Swerad also tends to overshoot low-level precipitating systems further away from the station, leading to an underestimation of snowfall rate and occasionally to missing precipitation altogether. Several statistical metrics - including the probability of detection, false alarm rate, hit rate, and Pierce's skill score - are calculated. The sensitivity of these metrics to the snowfall rate, as well as to the distance from the nearest radar station, are summarised. This highlights the strengths and the limitations of both observing systems at the lower and upper ends of the snowfall distributions as well as the range of uncertainties that can be expected from these systems in high-latitude regions.

  9. Detection and estimation of volcanic eruption onset and mass flow rate using weather radar and infrasonic array

    NASA Astrophysics Data System (ADS)

    Marzano, Frank S.; Mereu, Luigi; Montopoli, Mario; Picciotti, Errico; Di Fabio, Saverio; Bonadonna, Costanza; Marchetti, Emanuele; Ripepe, Maurizio

    2015-04-01

    The explosive eruption of sub-glacial Eyjafjallajökull volcano in 2010 was of modest size, but ash was widely dispersed over Iceland and Europe. The Eyjafjallajökull pulsating explosive activity started on April 14 and ended on May 22. The combination of a prolonged and sustained ejection of volcanic ash and persistent northwesterly winds resulted in dispersal the volcanic cloud over a large part of Europe. Tephra dispersal from an explosive eruption is a function of multiple factors, including magma mass flow rate (MFR), degree of magma fragmentation, vent geometry, plume height, particle size distribution (PSD) and wind velocity. One of the most important geophysical parameters, derivable from the analysis of tephra deposits, is the erupted mass, which is essential for the source characterization and assessment of the associated hazards. MFR can then be derived by dividing the erupted mass by the eruption duration (if known) or based on empirical and analytical relations with plume height. Microwave weather radars at C and X band can provide plume height, ash concentration and loading, and, to some extent, PSD and MFR. Radar technology is well established and can nowadays provide fast three-dimensional (3D) scanning antennas together with Doppler and dual polarization capabilities. However, some factors can limit the detection and the accuracy of the radar products aforementioned. For example, the sensitivity of microwave radar measurements depends on the distance between the radar antenna and the target, the transmitter central wavelength, receiver minimum detachable power and the resolution volume. In addition, radar measurements are sensitive to particle sizes larger than few tens of microns thus limiting the radar-based quantitative estimates to the larger portion of the PSD. Volcanic activity produces infrasonic waves (i.e., acoustic waves below 20 Hz), which can propagate in the atmosphere useful for the remote monitoring of volcanic activity. Infrasound associated with explosive eruptions is generally produced by the rapid expansion of the gas-particle mixture within the conduit and, in consequence, it is related to the dynamics of the volume outflow and thus to the intensity of the eruption. Infrasound is closely linked to the magma fragmentation process. By combining data from ground surveys and remote sensing measurements, it is possible to gain more insights into tephra detection and distribution. Microwave scanning radars can be exploited to extract tephra spatial-temporal distribution in proximity of the volcano vent. Radar detection of ash clouds is a cumbersome problem, as their signature can be confused with that of hydrometeors. On the other hand, infrasonic arrays can provide a very accurate signal about the onset of a volcanic fountain, even though not necessarily discriminating between lava and ash eruptions. In this work we illustrate the methodology to combine microwave radar data with infrasonic measurements using, as a case study, the eruption of 2010 Eyjafjallajökull. The probabilistic detection module of the Volcanic Ash Radar Retrieval (VARR) physically-based technique is illustrated. The ash detection methodology is based on the temporal analysis of radar volumes of reflectivity and geographical information for the considered specific area. The infrasonic array signal is coupled with radar data to enhance the VARR probability of ash detection. Moreover, mass flow rates estimated from radar measurements are compared with those retrieved from infrasonic arrays and derived from simplified analytical eruption models.

  10. Analysis of airborne Doppler lidar, Doppler radar and tall tower measurements of atmospheric flows in quiescent and stormy weather

    NASA Technical Reports Server (NTRS)

    Bluestein, H. B.; Doviak, R. J.; Eilts, M. D.; Mccaul, E. W.; Rabin, R.; Sundara-Rajan, A.; Zrnic, D. S.

    1986-01-01

    The first experiment to combine airborne Doppler Lidar and ground-based dual Doppler Radar measurements of wind to detail the lower tropospheric flows in quiescent and stormy weather was conducted in central Oklahoma during four days in June-July 1981. Data from these unique remote sensing instruments, coupled with data from conventional in-situ facilities, i.e., 500-m meteorological tower, rawinsonde, and surface based sensors, were analyzed to enhance understanding of wind, waves and turbulence. The purposes of the study were to: (1) compare winds mapped by ground-based dual Doppler radars, airborne Doppler lidar, and anemometers on a tower; (2) compare measured atmospheric boundary layer flow with flows predicted by theoretical models; (3) investigate the kinematic structure of air mass boundaries that precede the development of severe storms; and (4) study the kinematic structure of thunderstorm phenomena (downdrafts, gust fronts, etc.) that produce wind shear and turbulence hazardous to aircraft operations. The report consists of three parts: Part 1, Intercomparison of Wind Data from Airborne Lidar, Ground-Based Radars and Instrumented 444 m Tower; Part 2, The Structure of the Convective Atmospheric Boundary Layer as Revealed by Lidar and Doppler Radars; and Part 3, Doppler Lidar Observations in Thunderstorm Environments.

  11. The global space-time cascade structure of Precipitation: gauges, reanalyses, and satellite radar data: weather and climate scales

    NASA Astrophysics Data System (ADS)

    Lovejoy, Shaun; Stolle, Jonathan; Schertzer, Daniel

    2010-05-01

    There have been surprisingly few studies of the global space-time scaling properties of rain. One of the reasons is the difficulty in obtaining appropriate areal rainfall estimates: global gauge networks are sparse whereas individual land based radar measure effective reflectivity factors (not rain rates) and -except for the TRMM satellite radar - are limited to regions of only several hundred kilometres. Both radar and in situ measurements have difficulty distinguishing between low and zero rain rates. In comparison, meteorological reanalyses are on regular grids the result of using data assimilation algorithms. These are sophisticated model/data products but the assumptions needed to obtain rainfields are particularly questionable. In order to overcome these difficulties, it is therefore important to quantitatively compare the space-time scaling properties of data of each type (gauges, reanalyses, satellite radar). In this talk, we use 1) a unique in situ, precipitation product: the CPC gridded (hourly, 29 year long, 13x21 grid boxes, resolution roughly 200 km), 2) the state of the art ECMWF interim reanalysis "stratiform rain" product (3 hourly over 3 months, 1.5o resolution), as well as 3) 5300 orbits (1 year) of TRMM precipitation radar data gridded at 100x100 km, 4 day resolution. All three data sets were systematically analyzed in space (both east-west, and north-south), weak and strong events, collectively spanning scales a hundred kilometres to planetary and in time from hours to 30 years. This allowed us to determine their cascade structures and to make detailed scale by scale intercomparisons. In space, the cascades all had similar effective outer scales (around 30,000 km), with the east-west value a bit higher than the north-south value. In time both the CPC and the reanalyses had outer scales of about 50 days; however the TRMM radar data had an outer scale closer to 500, and larger than observed for other atmospheric fields. By quantitative comparison of exponents for low and high moments we showed that linear space-time transformations worked well for TRMM and the ECMWF reanalysis, less well for the CPC gauge data. We also could use this the analyses to statistically calibrate the TRMM radar.

  12. By Air and Land: Estimating Post-Fire Debris-Flow Susceptibility through High-Resolution Radar Reflectivity and Tipping-Bucket Gage Rainfall

    NASA Astrophysics Data System (ADS)

    Hanshaw, M. N.; Schmidt, K. M.; Jorgensen, D. P.; Stock, J. D.

    2008-12-01

    Wildfires often increase the occurrence of post-fire hazardous flash floods and debris flows from steeplands during intense rainfall. Rainfall intensity-duration thresholds have been used to forecast when this hazard increases rapidly; one threshold for Southern California is 15 mm/hr. However, such thresholds are usually developed with point measurements that only capture a small portion of the landscape. In an attempt to limit potential loss of life, the USGS is collaborating with NOAA on a demonstration early-warning system. To address the lack of spatial rainfall coverage, NOAA deployed a small mobile radar truck (SMART-R) to the Day fire in the western Transverse Range during the 2006-07 winter, and to the Canyon and Corral fires in the Santa Monica Mountains near Malibu during the 2007-08 winter. The SMART-R's C-band Doppler radar can be used to estimate rainfall rates over entire burned areas. On topography susceptible to debris flows within these 3 fires, the USGS installed a dense array of ground-based instruments, including 8 tipping- bucket rain gages in the Day fire, and 3 each in the Canyon and Corral fires. After converting hourly time- step grids of SMART-R reflectivity (150 m node spacing) into precipitation estimates, we compared the gage data to its spatially coincident SMART-R cell.Results from the Day fire indicate that SMART-R derived seasonal and event-based rainfall totals were typically greater than gage totals during the 2006-07 winter of record-low rainfall. Both data sets, however, reflected similar spatial patterns of rainfall intensity. In contrast, for the Malibu fires there is no systematic agreement in spatial pattern or rainfall mismatch; the difference between the two data sets. Of the 9 storms recorded during this 2007-08 winter, SMART-R estimates of rainfall totals exceeded the gage totals for only 3, underestimating totals for the remaining 6. The mismatch magnitudes also exceed that of the previous winter recorded at the Day fire, and, for the largest storm of the season, was 129 mm less than a rain gage total.These discrepancies reduce the reliability of a potential SMART-R-advised warning system, assuming truth from ground-based gages. During the 2007-08 winter near Malibu the rain gages recorded that the 15 mm/hr warning threshold was exceeded during only one storm, and only at one gage in the Corral fire. This event transported large amounts of sediment that resulted in road closures, and it produced at least one "firehose" debris flow generated by runoff from steep, exposed bedrock. In contrast, SMART-R derived rainfall intensities exceeded this threshold at all gage locations for 2 of the 3 storms with overestimated rainfall intensities. It underestimated rainfall intensities for the 6 remaining storms; such underestimates could have led to potential false negatives, which are of concern for preserving human life.It is not yet clear which storms are amenable to the use of SMART-R technology for capturing spatial estimates of rainfall intensity, but results from the Day fire showing topographically forced rainfall patterns support validity of the system. Future work needs to address discrepancies arising from comparing spatially continuous atmospheric radar measurements with terrestrial point measurements. One effort to mitigate some interpretation complexities could include the installation of a disdrometer along with the rain gages, to measure rain drop-size distributions to calibrate in near real-time the relation between measured reflectivity and inferred rainfall.

  13. Comparison of Two Methods for Estimating the Sampling-Related Uncertainty of Satellite Rainfall Averages Based on a Large Radar Data Set

    NASA Technical Reports Server (NTRS)

    Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.

    2002-01-01

    The uncertainty of rainfall estimated from averages of discrete samples collected by a satellite is assessed using a multi-year radar data set covering a large portion of the United States. The sampling-related uncertainty of rainfall estimates is evaluated for all combinations of 100 km, 200 km, and 500 km space domains, 1 day, 5 day, and 30 day rainfall accumulations, and regular sampling time intervals of 1 h, 3 h, 6 h, 8 h, and 12 h. These extensive analyses are combined to characterize the sampling uncertainty as a function of space and time domain, sampling frequency, and rainfall characteristics by means of a simple scaling law. Moreover, it is shown that both parametric and non-parametric statistical techniques of estimating the sampling uncertainty produce comparable results. Sampling uncertainty estimates, however, do depend on the choice of technique for obtaining them. They can also vary considerably from case to case, reflecting the great variability of natural rainfall, and should therefore be expressed in probabilistic terms. Rainfall calibration errors are shown to affect comparison of results obtained by studies based on data from different climate regions and/or observation platforms.

  14. Developing Dual Polarization Applications For 45th Weather Squadron's (45 WS) New Weather Radar: A Cooperative Project With The National Space Science and Technology Center (NSSTC)

    NASA Technical Reports Server (NTRS)

    Roeder, W.P.; Peterson, W.A.; Carey, L.D.; Deierling, W.; McNamara, T.M.

    2009-01-01

    A new weather radar is being acquired for use in support of America s space program at Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick AFB on the east coast of central Florida. This new radar includes dual polarization capability, which has not been available to 45 WS previously. The 45 WS has teamed with NSSTC with funding from NASA Marshall Spaceflight Flight Center to improve their use of this new dual polarization capability when it is implemented operationally. The project goals include developing a temperature profile adaptive scan strategy, developing training materials, and developing forecast techniques and tools using dual polarization products. The temperature profile adaptive scan strategy will provide the scan angles that provide the optimal compromise between volume scan rate, vertical resolution, phenomena detection, data quality, and reduced cone-of-silence for the 45 WS mission. The mission requirements include outstanding detection of low level boundaries for thunderstorm prediction, excellent vertical resolution in the atmosphere electrification layer between 0 C and -20 C for lightning forecasting and Lightning Launch Commit Criteria evaluation, good detection of anvil clouds for Lightning Launch Commit Criteria evaluation, reduced cone-of-silence, fast volume scans, and many samples per pulse for good data quality. The training materials will emphasize the appropriate applications most important to the 45 WS mission. These include forecasting the onset and cessation of lightning, forecasting convective winds, and hopefully the inference of electrical fields in clouds. The training materials will focus on annotated radar imagery based on products available to the 45 WS. Other examples will include time sequenced radar products without annotation to simulate radar operations. This will reinforce the forecast concepts and also allow testing of the forecasters. The new dual polarization techniques and tools will focus on the appropriate applications for the 45 WS mission. These include forecasting the onset of lightning, the cessation of lightning, convective winds, and hopefully the inference of electrical fields in clouds. This presentation will report on the results achieved so far in the project.

  15. Application of weather radar to the basaltic phreatomagmatic eruption in Grímsvötn in 2004, comparison with models of plume transport

    NASA Astrophysics Data System (ADS)

    Oddsson, B.; Gudmundsson, M. T.; Larsen, G.; Karlsdottir, S.

    2009-12-01

    Weather radar data has been used to monitor volcanic plumes but comparison of these data with direct measurements of plume height have been few, at least for basaltic eruption. The phreatomagmatic eruption in Grímsvötn in 2004 was monitored by weather radar and some measurements of plume height were also made from aircraft. The main phase of the eruption lasted for 33 hours and an almost continuous record was obtained by the radar, located in Keflavík, 260 km to the west of the volcano. During this period the eruption plume reached 6-10 km height relative to the vent. Comparison of the radar measurements of plume height and direct measurements from aircraft suggests that atmospheric super-refraction can cause bending of the radar beam towards the Earth. This leads to a systematic overestimate of plume height by the radar. Visual inspection indicates that apparent oscillation in plume height indicated by the radar record, is greatly exaggerated. The radar beam width increases with distance and is about 4 km over Grímsvötn, resulting in a 2 km uncertanty in plume height determination, and the discrete stepping in elevation angles of the radar is the most likely cause of the apparent fluctuation of 2-4 km in plume height. These shortcomings due to long distance errors underpin the need for the installation of a second weather radar in North-East Iceland, to provide adequate cover for eruptions within Vatnajökull. The measured tephra mass of the eruption can be compared with predictions from theoretical and empirical models relating plume height and mass transport. These models predict 2-4 times greater mass flux than observed in the erupion. Although the error margins are considerable, this suggests that these models overestimate the transport by basaltic phreatomagmatic eruptions.

  16. Evaluation of radar rainfall estimates and nowcasts to prevent flash flood in real time by using a road submersion warning tool

    NASA Astrophysics Data System (ADS)

    Versini, Pierre-Antoine; Sempere-Torres, Daniel

    2010-05-01

    Important damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions. These are major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods and different kinds of rainfall observations are available in real time: radar rainfall estimates and nowcasts from METEO FRANCE and the CALAMAR system from SPC (state authority in charge of flood forecasting). An application devoted to the road network, has also been recently developed for this region. It combines distributed hydro-meteorological very short range forecasts and vulnerability analysis to provide warnings of road submersions. The first results demonstrate that it is technically possible to provide distributed short-term forecasts for a large number of sites. The study also demonstrates that a reliable estimation of the spatial distribution of rainfall is essential. For this reason, the road submersion warning system can be used to evaluate the quality of rainfall estimates and nowcasts. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, more than 300mm dropped on the South part of the Gard and many roads were submerged. Each of the mentioned rainfall datasets (i.e. estimates and nowcasts) was available in real time. They have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. The results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and a reasonable false alarm ratio. It demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall nowcasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding one hour.

  17. A nonlinear spatio-temporal lumping of radar rainfall for modeling multi-step-ahead inflow forecasts by data-driven techniques

    NASA Astrophysics Data System (ADS)

    Chang, Fi-John; Tsai, Meng-Jung

    2016-04-01

    Accurate multi-step-ahead inflow forecasting during typhoon periods is extremely crucial for real-time reservoir flood control. We propose a spatio-temporal lumping of radar rainfall for modeling inflow forecasts to mitigate time-lag problems and improve forecasting accuracy. Spatial aggregation of radar cells is made based on the sub-catchment partitioning obtained from the Self-Organizing Map (SOM), and then flood forecasting is made by the Adaptive Neuro Fuzzy Inference System (ANFIS) models coupled with a 2-staged Gamma Test (2-GT) procedure that identifies the optimal non-trivial rainfall inputs. The Shihmen Reservoir in northern Taiwan is used as a case study. The results show that the proposed methods can, in general, precisely make 1- to 4-hour-ahead forecasts and the lag time between predicted and observed flood peaks could be mitigated. The constructed ANFIS models with only two fuzzy if-then rules can effectively categorize inputs into two levels (i.e. high and low) and provide an insightful view (perspective) of the rainfall-runoff process, which demonstrate their capability in modeling the complex rainfall-runoff process. In addition, the confidence level of forecasts with acceptable error can reach as high as 97% at horizon t+1 and 77% at horizon t+4, respectively, which evidently promotes model reliability and leads to better decisions on real-time reservoir operation during typhoon events.

  18. Range profiling of the rain rate by an airborne weather radar

    NASA Technical Reports Server (NTRS)

    Meneghini, Robert; Nakamura, Kenji

    1990-01-01

    A class of methods based on a measure of path attenuation that is used to constrain the Hitschfeld-Bordan solution is investigated. Such methods are investigated for lidar, radar, and combined radar-radiometer applications. Their function is to allocate the attenuation in proportion to the strength of the measured reflectivity. A description is provided of four estimates of rain rate that have been tested using data from a dual-wavelength airborne radar at 10 GHz and 35 GHz. It is concluded, that when attenuation is significant, the estimates are generally more accurate than those without attenuation correction. Thus, such methodologies can be utilized to extend the effective dynamic range of the radar to higher rain rates.

  19. High resolution fire danger modeling : integration of quantitative precipitation amount estimates derived from weather radars as an input of FWI

    NASA Astrophysics Data System (ADS)

    Cloppet, E.; Regimbeau, M.

    2009-09-01

    Fire meteo indices provide efficient guidance tools for the prevention, early warning and surveillance of forest fires. The indices are based on meteorological input data. The underlying approach is to exploit meteorological information as fully as possible to model the soil water content, biomass condition and fire danger. Fire meteorological danger is estimated by Météo-France at national level through the use of Fire Weather Index. The fire index services developed within the PREVIEW project (2005-2008) offer for the first time very high resolution mapping of forest fire risk. The high resolution FWI has been implemented in France complementary to the existing EFFIS operated by the Joint Research Center. A new method (ANTILOPE method) of combining precipitation data originating from different sources like rain gauges and weather radar measurements has been applied in the new service. Some of the advantages of this new service are: · Improved detection of local features of fire risk · More accurate analysis of meteorological input data used in forest fire index models providing added value for forest fire risk forecasts · Use of radar precipitation data "as is” utilizing the higher resolution, i.e. avoiding averaging operations The improved accuracy and spatial resolution of the indices provide a powerful early warning tool for national and regional civil protection and fire fighting authorities to alert and initiate forest fire fighting actions and measures.

  20. Adaptive clutter rejection filters for airborne Doppler weather radar applied to the detection of low altitude windshear

    NASA Technical Reports Server (NTRS)

    Keel, Byron M.

    1989-01-01

    An optimum adaptive clutter rejection filter for use with airborne Doppler weather radar is presented. The radar system is being designed to operate at low-altitudes for the detection of windshear in an airport terminal area where ground clutter returns may mask the weather return. The coefficients of the adaptive clutter rejection filter are obtained using a complex form of a square root normalized recursive least squares lattice estimation algorithm which models the clutter return data as an autoregressive process. The normalized lattice structure implementation of the adaptive modeling process for determining the filter coefficients assures that the resulting coefficients will yield a stable filter and offers possible fixed point implementation. A 10th order FIR clutter rejection filter indexed by geographical location is designed through autoregressive modeling of simulated clutter data. Filtered data, containing simulated dry microburst and clutter return, are analyzed using pulse-pair estimation techniques. To measure the ability of the clutter rejection filters to remove the clutter, results are compared to pulse-pair estimates of windspeed within a simulated dry microburst without clutter. In the filter evaluation process, post-filtered pulse-pair width estimates and power levels are also used to measure the effectiveness of the filters. The results support the use of an adaptive clutter rejection filter for reducing the clutter induced bias in pulse-pair estimates of windspeed.

  1. Country-wide rainfall maps from a commercial cellular telephone network

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2012-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for many applications, for instance, as input for hydrological models. Weather radars often provide data with sufficient spatial and temporal resolution, but usually need adjustment. In general, only few rain gauge measurements are available to adjust the radar data in real-time, for example, each hour. Physically based methods, such as a VPR correction, can be valuable and hold a promise. However, they are not always performed in real-time yet and can be difficult to implement. The estimation of rainfall using microwave links from commercial cellular telephone networks is a new and potentially valuable source of information. Such networks cover large parts of the land surface of the earth and have a high density. The data produced by the microwave links in such networks is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A recent study of us shows that urban rainfall can be estimated from commercial microwave link data for the Rotterdam region, a densely-populated delta city in the Netherlands. A data set from a commercial microwave link network over the Netherlands is analyzed, containing approximately 1500 links covering the land surface of the Netherlands (35500 km2). This data set consists of several days with extreme rainfall in June, July and August 2011. A methodology is presented to derive rainfall intensities and daily rainfall depths from the microwave link data, which have a temporal resolution of 15 min. The magnitude and dynamics of these rainfall intensities is compared with those obtained from weather radar. Rainfall maps are derived from the microwave link data and are verified against rainfall maps based on gauge-adjusted weather radar data. Although much more work needs to be done, the first results look promising. Since cellular telephone networks are used worldwide, data from such networks could also become a valuable source of rainfall information in countries which do not have continuously operating weather radars, and no or few rain gauges. Apart from rainfall maps which are solely based on microwave link data, a preliminary analysis will be presented to assess whether commercial microwave link data can be used to adjust radar rainfall accumulations.

  2. Methods of Attenuation Correction for Dual-Wavelength and Dual-Polarization Weather Radar Data

    NASA Technical Reports Server (NTRS)

    Meneghini, R.; Liao, L.

    2007-01-01

    In writing the integral equations for the median mass diameter and number concentration, or comparable parameters of the raindrop size distribution, it is apparent that the forms of the equations for dual-polarization and dual-wavelength radar data are identical when attenuation effects are included. The differential backscattering and extinction coefficients appear in both sets of equations: for the dual-polarization equations, the differences are taken with respect to polarization at a fixed frequency while for the dual-wavelength equations, the differences are taken with respect to frequency at a fixed polarization. An alternative to the integral equation formulation is that based on the k-Z (attenuation coefficient-radar reflectivity factor) parameterization. This-technique was originally developed for attenuating single-wavelength radars, a variation of which has been applied to the TRMM Precipitation Radar data (PR). Extensions of this method have also been applied to dual-polarization data. In fact, it is not difficult to show that nearly identical equations are applicable as well to dualwavelength radar data. In this case, the equations for median mass diameter and number concentration take the form of coupled, but non-integral equations. Differences between this and the integral equation formulation are a consequence of the different ways in which attenuation correction is performed under the two formulations. For both techniques, the equations can be solved either forward from the radar outward or backward from the final range gate toward the radar. Although the forward-going solutions tend to be unstable as the attenuation out to the range of interest becomes large in some sense, an independent estimate of path attenuation is not required. This is analogous to the case of an attenuating single-wavelength radar where the forward solution to the Hitschfeld-Bordan equation becomes unstable as the attenuation increases. To circumvent this problem, the equations can be expressed in the form of a final-value problem so that the recursion begins at the far range gate and proceeds inward towards the radar. Solving the problem in this way traditionally requires estimates of path attenuation to the final gate: in the case of orthogonal linear polarizations, the attenuations at horizontal and vertical polarizations (same frequency) are required while in the dual-wavelength case, attenuations at the two frequencies (same polarization) are required.

  3. Flash flood warning in mountaineous areas using X-band weather radars and the AIGA method in the framework of the RHYTMME project

    NASA Astrophysics Data System (ADS)

    Javelle, Pierre; Defrance, Dimitri; Ecrepont, Stéphane; Fouchier, Catherine; Mériaux, Patrice; Tolsa, Mathieu; Westrelin, Samuel

    2013-04-01

    The knowledge of precipitations still remains a tricky issue in mountaineous areas: the available rain-gauges are in a limited number and most often located in the valleys, and the radar rainfall estimates have to deal with a lot of problems due to the relief and the difficulty to distinguish the different types of hydrometeors (snow, hail, rain). In this context, the "RHYTMME" project deals with two main issues: - Providing an accurate radar rainfall information in mountainous areas. - Developing a real-time hazards warning system based on this information. To answer to the first issue, a X-band doppler dual polarized radar network is currently implemented in the French South Alps. At the end of the project (2013), three new radars will be installed, completing a pre-existing radar already installed on the Mont Vial top since 2008 (Hydrix® technology developed by the Novimet company, and tested in a previous project). The present communication focuses on the flash flood warning issue. It presents some results obtained by coupling the radar estimates to a simple distributed hydrological model (the AIGA method). Results are compared on damages observed by end-users, which were strongly involved into the project. The RHYTMME project is co-piloted by Meteo-France and the Cemagref and has the financial support of the European Union, the Provence-Alpes-Côte d'Azur Region and the French Ministry in charge of Ecology.

  4. Assessment of Rainfall Estimates Using a Standard Z-R Relationship and the Probability Matching Method Applied to Composite Radar Data in Central Florida

    NASA Technical Reports Server (NTRS)

    Crosson, William L.; Duchon, Claude E.; Raghavan, Ravikumar; Goodman, Steven J.

    1996-01-01

    Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from flash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 30OR(sup 1.4) (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching method (PMM). Rainfall derived from the power law Z-R was found to he highly biased (+90%-l10%) compared to rain gauge measurements for various temporal and spatial integrations. Application of a 36.5-dBZ reflectivity threshold (determined via the PMM) was found to improve the performance of the power law Z-R, reducing the biases substantially to 20%-33%. Correlations between precipitation estimates obtained with either Z-R relationship and mean gauge values are much higher for areal averages than for point locations. Precipitation estimates from the PMM are an improvement over those obtained using the power law in that biases and root-mean-square errors are much lower. The minimum timescale for application of the PMM with the composite radar dataset was found to be several days for area-average precipitation. The minimum spatial scale is harder to quantify, although it is concluded that it is less than 350 sq km. Implications relevant to the WSR-88D system are discussed.

  5. Radar QPE for hydrological design: Intensity-Duration-Frequency curves

    NASA Astrophysics Data System (ADS)

    Marra, Francesco; Morin, Efrat

    2015-04-01

    Intensity-duration-frequency (IDF) curves are widely used in flood risk management since they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. They are estimated analyzing the extreme values of rainfall records, usually basing on raingauge data. This point-based approach raises two issues: first, hydrological design applications generally need IDF information for the entire catchment rather than a point, second, the representativeness of point measurements decreases with the distance from measure location, especially in regions characterized by steep climatological gradients. Weather radar, providing high resolution distributed rainfall estimates over wide areas, has the potential to overcome these issues. Two objections usually restrain this approach: (i) the short length of data records and (ii) the reliability of quantitative precipitation estimation (QPE) of the extremes. This work explores the potential use of weather radar estimates for the identification of IDF curves by means of a long length radar archive and a combined physical- and quantitative- adjustment of radar estimates. Shacham weather radar, located in the eastern Mediterranean area (Tel Aviv, Israel), archives data since 1990 providing rainfall estimates for 23 years over a region characterized by strong climatological gradients. Radar QPE is obtained correcting the effects of pointing errors, ground echoes, beam blockage, attenuation and vertical variations of reflectivity. Quantitative accuracy is then ensured with a range-dependent bias adjustment technique and reliability of radar QPE is assessed by comparison with gauge measurements. IDF curves are derived from the radar data using the annual extremes method and compared with gauge-based curves. Results from 14 study cases will be presented focusing on the effects of record length and QPE accuracy, exploring the potential application of radar IDF curves for ungauged locations and providing insights on the use of radar QPE for hydrological design studies.

  6. The Use of Radar-Based Products for Deriving Extreme Rainfall Frequencies Using Regional Frequency Analysis with Application in South Louisiana

    NASA Astrophysics Data System (ADS)

    El-Dardiry, H. A.; Habib, E. H.

    2014-12-01

    Radar-based technologies have made spatially and temporally distributed quantitative precipitation estimates (QPE) available in an operational environmental compared to the raingauges. The floods identified through flash flood monitoring and prediction systems are subject to at least three sources of uncertainties: (a) those related to rainfall estimation errors, (b) those due to streamflow prediction errors due to model structural issues, and (c) those due to errors in defining a flood event. The current study focuses on the first source of uncertainty and its effect on deriving important climatological characteristics of extreme rainfall statistics. Examples of such characteristics are rainfall amounts with certain Average Recurrence Intervals (ARI) or Annual Exceedance Probability (AEP), which are highly valuable for hydrologic and civil engineering design purposes. Gauge-based precipitation frequencies estimates (PFE) have been maturely developed and widely used over the last several decades. More recently, there has been a growing interest by the research community to explore the use of radar-based rainfall products for developing PFE and understand the associated uncertainties. This study will use radar-based multi-sensor precipitation estimates (MPE) for 11 years to derive PFE's corresponding to various return periods over a spatial domain that covers the state of Louisiana in southern USA. The PFE estimation approach used in this study is based on fitting generalized extreme value distribution to hydrologic extreme rainfall data based on annual maximum series (AMS). Some of the estimation problems that may arise from fitting GEV distributions at each radar pixel is the large variance and seriously biased quantile estimators. Hence, a regional frequency analysis approach (RFA) is applied. The RFA involves the use of data from different pixels surrounding each pixel within a defined homogenous region. In this study, region of influence approach along with the index flood technique are used in the RFA. A bootstrap technique procedure is carried out to account for the uncertainty in the distribution parameters to construct 90% confidence intervals (i.e., 5% and 95% confidence limits) on AMS-based precipitation frequency curves.

  7. Estimation of areal precipitation based on rainfall data and X-band radar images in the Venero-Claro Basin (Ávila, Spain)

    NASA Astrophysics Data System (ADS)

    Guardiola-Albert, Carolina; River-Honegger, Carlos; Yagüe, Carlos; Agut, Robert Monjo i.; Díez-Herrero, Andrés; María Bodoque, José; José Tapiador, Francisco

    2015-04-01

    The aim of this work is to estimate the spatial-temporal rainfall during precipitation events with hydrological response in Venero-Claro Basin (Avila, Spain). In this small mountainous basin of 15km2, flood events of different magnitudes have been often registered. Therefore, rainfall estimation is essential to calibrate and validate hydrological models, and hence implies an improvement in the objectivity of risk studies and its predictive and preventive capacity. The geostatistical merging method of ordinary kriging of the errors (OKRE) has been applied. This technique has been already used by several authors to merge C-band radar and dense rain gauge networks. Here it is adapted to estimate hourly rainfall accumulations over the area with observations from one of the 5 existing X-band radar in Spain and 7 rain gauges located in the zone. Verification of the results has been performed through cross-validation comparing the estimation error of the OKRE with the one obtained adjusting the Marshall-Palmer relation. Analyzed errors are bias, the Hanseen-Kuiper coefficient and the relative mean root transformed error. Results have an average error of 15%, distinguishing quite well between dry and wet periods.

  8. Detection of Digital Elevation Model Errors Using X-band Weather Radar

    NASA Technical Reports Server (NTRS)

    Young, Steven D.; deHaag, Maatren Uijt

    2007-01-01

    Flight in Instrument Meteorological Conditions requires pilots to manipulate flight controls while referring to a Primary Flight Display. The Primary Flight Display indicates aircraft attitude along with, in some cases, many other state variables such as altitude, speed, and guidance cues. Synthetic Vision Systems have been proposed that overlay the traditional information provided on Primary Flight Displays onto a scene depicting the location of terrain and other geo-spatial features.Terrain models used by these displays must have sufficient quality to avoid providing misleading information. This paper describes how X-band radar measurements can be used as part of a monitor, and/or maintenance system, to quantify the integrity of terrain models that are used by systems such as Synthetic Vision. Terrain shadowing effects, as seen by the radar, are compared in a statistical manner against estimated shadow feature elements extracted from the stored terrain model from the perspective of the airborne observer. A test statistic is defined that enables detection of errors as small as the range resolution of the radar. Experimental results obtained from two aircraft platforms hosting certified commercial-off-the-shelf X-band radars test the premise and illustrate its potential.

  9. Doppler weather radar observations of the 2009 eruption of Redoubt Volcano, Alaska

    USGS Publications Warehouse

    Schneider, David J.; Hoblitt, Richard P.

    2013-01-01

    The U.S. Geological Survey (USGS) deployed a transportable Doppler C-band radar during the precursory stage of the 2009 eruption of Redoubt Volcano, Alaska that provided valuable information during subsequent explosive events. We describe the capabilities of this new monitoring tool and present data captured during the Redoubt eruption. The MiniMax 250-C (MM-250C) radar detected seventeen of the nineteen largest explosive events between March 23 and April 4, 2009. Sixteen of these events reached the stratosphere (above 10 km) within 2–5 min of explosion onset. High column and proximal cloud reflectivity values (50 to 60 dBZ) were observed from many of these events, and were likely due to the formation of mm-sized accretionary tephra-ice pellets. Reflectivity data suggest that these pellets formed within the first few minutes of explosion onset. Rapid sedimentation of the mm-sized pellets was observed as a decrease in maximum detection cloud height. The volcanic cloud from the April 4 explosive event showed lower reflectivity values, due to finer particle sizes (related to dome collapse and related pyroclastic flows) and lack of significant pellet formation. Eruption durations determined by the radar were within a factor of two compared to seismic and pressure-sensor derived estimates, and were not well correlated. Ash dispersion observed by the radar was primarily in the upper troposphere below 10 km, but satellite observations indicate the presence of volcanogenic clouds in the stratosphere. This study suggests that radar is a valuable complement to traditional seismic and satellite monitoring of explosive eruptions.

  10. Characterizing response of total suspended solids and total phosphorus loading to weather and watershed characteristics for rainfall and snowmelt events in agricultural watersheds

    USGS Publications Warehouse

    Danz, Mari E.; Corsi, Steven; Brooks, Wesley R.; Bannerman, Roger T.

    2013-01-01

    Understanding the response of total suspended solids (TSS) and total phosphorus (TP) to influential weather and watershed variables is critical in the development of sediment and nutrient reduction plans. In this study, rainfall and snowmelt event loadings of TSS and TP were analyzed for eight agricultural watersheds in Wisconsin, with areas ranging from 14 to 110 km2 and having four to twelve years of data available. The data showed that a small number of rainfall and snowmelt runoff events accounted for the majority of total event loading. The largest 10% of the loading events for each watershed accounted for 73–97% of the total TSS load and 64–88% of the total TP load. More than half of the total annual TSS load was transported during a single event for each watershed at least one of the monitored years. Rainfall and snowmelt events were both influential contributors of TSS and TP loading. TSS loading contributions were greater from rainfall events at five watersheds, from snowmelt events at two watersheds, and nearly equal at one watershed. The TP loading contributions were greater from rainfall events at three watersheds, from snowmelt events at two watersheds and nearly equal at three watersheds. Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors. All individual models and the combined model for rainfall events resulted in two common predictors as most influential for TSS and TP. These included rainfall depth and the antecedent baseflow. Using these two predictors alone resulted in an R2 greater than 0.7 in all but three individual models and 0.61 or greater for all individual models. The combined model yielded an R2 of 0.66 for TSS and 0.59 for TP. Neither the individual nor the combined models were substantially improved by using additional predictors. Snowmelt event models were statistically significant for individual and combined watershed models, but the model fits were not all as good as those for rainfall events (R2 between 0.19 and 0.87). Predictor selection varied from watershed to watershed, and the common variables that were selected were not always selected in the same order. Influential variables were commonly direct measures of moisture in the watershed such as snowmelt, rainfall + snowmelt, and antecedent baseflow, or measures of potential snowmelt volume in the watershed such as air temperature.

  11. On the Tropical Rainfall Measuring Mission (TRMM): Bringing NASA's Earth System Science Program to the Classroom

    NASA Technical Reports Server (NTRS)

    Shepherd, J. Marshall

    1998-01-01

    The Tropical Rainfall Measuring Mission is the first mission dedicated to measuring tropical and subtropical rainfall using a variety of remote sensing instrumentation, including the first spaceborne rain-measuring radar. Since the energy released when tropical rainfall occurs is a primary "fuel" supply for the weather and climate "engine"; improvements in computer models which predict future weather and climate states may depend on better measurements of global tropical rainfall and its energy. In support of the STANYS conference theme of Education and Space, this presentation focuses on one aspect of NASA's Earth Systems Science Program. We seek to present an overview of the TRMM mission. This overview will discuss the scientific motivation for TRMM, the TRMM instrument package, and recent images from tropical rainfall systems and hurricanes. The presentation also targets educational components of the TRMM mission in the areas of weather, mathematics, technology, and geography that can be used by secondary school/high school educators in the classroom.

  12. Time-dependent Second Order Scattering Theory for Weather Radar with a Finite Beam Width

    NASA Technical Reports Server (NTRS)

    Kobayashi, Satoru; Tanelli, Simone; Im, Eastwood; Ito, Shigeo; Oguchi, Tomohiro

    2006-01-01

    Multiple scattering effects from spherical water particles of uniform diameter are studied for a W-band pulsed radar. The Gaussian transverse beam-profile and the rectangular pulse-duration are used for calculation. An second-order analytical solution is derived for a single layer structure, based on a time-dependent radiative transfer theory as described in the authors' companion paper. When the range resolution is fixed, increase in footprint radius leads to increase in the second order reflectivity that is defined as the ratio of the second order return to the first order one. This feature becomes more serious as the range increases. Since the spaceborne millimeter-wavelength radar has a large footprint radius that is competitive to the mean free path, the multiple scattering effect must be taken into account for analysis.

  13. Assessment of the Doppler Radar for Airport Weather (DRAW) System in Japan as a Research Tool for Studying Typhoon

    NASA Astrophysics Data System (ADS)

    Kusunoki, Kenichi

    The purpose of this study is to demonstrate the usefulness of the Doppler Radar for Airport Weather (DRAW) system as a research tool for studying typhoon. I particularly aim at assessing opportunity for detecting typhoon inner core circulations and precipitations with the DRAW. For centers of typhoons, which correspond to positions of the inner cores, it is estimated that 322 hours of data (61cases) had been collected with the eight DRAWs over past 30 typhoons (1995-2005). On average, about one typhoon will be observed with each DRAW site. The Naha DRAW (the southernmost DRAW site) will provide the most frequent observations and each observed center would remain in radar range for periods between 4 and 11 hours. In this study, it is shown that many typhoon inner core cases will be collected with DRAW and suggested new opportunities for further research and development these phenomena. DRAWs will play an increasing role to understand detailed typhoon structures and life cycles (e.g., polygonal eyewall, mesovorticies, landfall processes, and asymmetric structure), and in the future, to improve typhoon intensity forecasts.

  14. Automatic detection of low altitude wind shear due to gust fronts in the terminal Doppler weather radar operational demonstration

    NASA Technical Reports Server (NTRS)

    Klingle-Wilson, Diana

    1990-01-01

    A gust front is the leading edge of the cold air outflow from a thunderstorm. Wind shears and turbulence along the gust front may produce potentially hazardous conditions for an aircraft on takeoff or landing such that runway operations are significantly impacted. The Federal Aviation Administration (FAA) has therefore determined that the detection of gust fronts in the terminal environment be an integral part of the Terminal Doppler Weather Radar (TDWR) system. Detection of these shears by the Gust Front Algorithm permits the generation of warnings that can be issued to pilots on approach and departure. In addition to the detection capability, the algorithm provides an estimate of the wind speed and direction following the gust front (termed wind shift) and the forecasted location of the gust front up to 20 minutes before it impacts terminal operations. This has shown utility as a runway management tool, alerting runway supervisors to approaching wind shifts and the possible need to change runway configurations. The formation and characteristics of gust fronts and their signatures in Doppler radar data are discussed. A brief description of the algorithm and its products for use by Air Traffic Control (ATC), along with an assessment of the algorithm's performance during the 1988 Operational Test and Evaluation, is presented.

  15. The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system

    NASA Technical Reports Server (NTRS)

    Hermes, Laurie G.; Witt, Arthur; Smith, Steven D.; Klingle-Wilson, Diana; Morris, Dale; Stumpf, Gregory J.; Eilts, Michael D.

    1993-01-01

    The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

  16. Using X-band Weather Radar Measurements to Monitor the Integrity of Digital Elevation Models for Synthetic Vision Systems

    NASA Technical Reports Server (NTRS)

    Young, Steve; UijtdeHaag, Maarten; Sayre, Jonathon

    2003-01-01

    Synthetic Vision Systems (SVS) provide pilots with displays of stored geo-spatial data representing terrain, obstacles, and cultural features. As comprehensive validation is impractical, these databases typically have no quantifiable level of integrity. Further, updates to the databases may not be provided as changes occur. These issues limit the certification level and constrain the operational context of SVS for civil aviation. Previous work demonstrated the feasibility of using a realtime monitor to bound the integrity of Digital Elevation Models (DEMs) by using radar altimeter measurements during flight. This paper describes an extension of this concept to include X-band Weather Radar (WxR) measurements. This enables the monitor to detect additional classes of DEM errors and to reduce the exposure time associated with integrity threats. Feature extraction techniques are used along with a statistical assessment of similarity measures between the sensed and stored features that are detected. Recent flight-testing in the area around the Juneau, Alaska Airport (JNU) has resulted in a comprehensive set of sensor data that is being used to assess the feasibility of the proposed monitor technology. Initial results of this assessment are presented.

  17. Forward Greedy ANN input selection in a stacked framework with Adaboost.RT - A streamflow forecasting case study exploiting radar rainfall estimates

    NASA Astrophysics Data System (ADS)

    Brochero, D.; Anctil, F.; Gagné, C.

    2012-04-01

    In input selection (or feature selection), modellers are interested in identifying k of the d dimensions that provide the most information. In hydrology, this problem is particularly relevant when dealing with temporally and spatially distributed data such as radar rainfall estimates or meteorological ensemble forecasts. The most common approaches for input determination of artifitial neural networks (ANN) in water resources are cross-correlation, heuristics, embedding window analysis (chaos theory), and sensitivity analyses. We resorted here to Forward Greedy Selection (FGS), a sensitivity analysis, for identifying the inputs that maximize the performance of ANN forecasting. It consists of a pool of ANNs with different structures, initial weights, and training data subsets. The stacked ANN model was setup through the joint use of stop training and a special type of boosting for regression known as AdaBoost.RT. Several ANN are then used in series, each one exploiting, with incremental probability, data with relative estimation error higher than a pre-set threshold value. The global estimate is then obtained from the aggregation of the estimates of the models (here the median value). Two schemes are compared here, which differ in their input type. The first scheme looks at lagged radar rainfall estimates averaged over entire catchment (the average scenario), while the second scheme deals with the spatial variation fields of the radar rainfall estimates (the distributed scenario). Results lead to three major findings. First, stacked ANN response outperforms the best single ANN (in the same way as many others reports). Second, a positive gain in the test subset of around 20%, when compared to the average scenario, is observed in the distributed scenario. However, the most important result from the selecting process is the final structure of the inputs, for the distributed scenario clearly outlines the areas with the greatest impact on forecasting in terms of the estimated radar precipitation and the forecast horizon. Thus, this research facilitates interpretability of the results under a downward approach, in which the zones of influence of rainfall at different forecasting horizons help understanding the pattern of the hydrologic response at the event scale. Third, the input selection is slightly different between experiments due to the active principle of diversity, defined as hydrological model complementarities addressing different aspects of the forecast. Finally the following guidelines favoured efficient stacked ANNs: i) design different combiners, ii) base the stack preprocess on probabilistic score representations oriented toward the bias of the ensemble (e.g. the ignorance score), and iii) evaluate more powerful multi-criterion selection algorithms such as multiobjective evolutionary algorithms (MOEA).

  18. Weather-type downscaling of seasonal predictions to daily rainfall characteristics over the Pacific-Andean basin of Ecuador and Peru

    NASA Astrophysics Data System (ADS)

    Pineda, Luis; Willems, Patrick

    2015-04-01

    A weather-type downscaling of seasonal predictions to daily rainfall characteristics is conducted over the Pacific-Andean region of Ecuador and Peru (PAEP) in NW South-America using a non homogenous hidden Markov model (NHMM) and retrospective seasonal information from general circulation models (GCMs). First, a HMM is used to diagnose four states which play distinct roles in the Dec-May rainy season. The estimated daily-states fall into one pair of wet states, one dry and one transitional dry/wet state, and show a systematic seasonal evolution together with intra-seasonal and inter-annual variability. The first wet-state represents region-wide wet conditions, while the second one represents north-south gradients. The former could be associated with the annual moisture off-shore the PAEP region, thermally driven by the climatological maximum of sea surface temperatures in El Niño 1.2 region. The latter corresponded with the dynamically noisy component of the PAEP rainfall signal, associated with the annual displacement of the Inter-tropical convergence zone. Then, a 4-state NHMM is coupled with GCM information to simulate daily sequences at each station. Simulations of the GCM-NHMM approach represent well daily rainfall characteristics at station level. The best skills were found in reproducing the inter-annual variation of seasonal rainfall amount and mean intensity at regional-averaged level with correlations equals to 0.60 and 0.64, respectively.

  19. Evaluation of the hydrologic measure quality of the Saint Nizier weather radar data on the local urban area of Greater Lyon

    NASA Astrophysics Data System (ADS)

    Renard, F.; Faure, D.; Comby, J.

    2009-04-01

    The meteorological radar of Saint Nizier d'Azergues, part of Meteo France network Aramis, is situated at only 40 km from the urban community of Greater Lyon, in the north of the Rhne valley, south-east of France. This area gathers many human, environmental and materials stakes and vulnerability. From an operational use, an assessment based on a simulation and analysis of real data has identified certain sectors of the community affected by problems of ground clutter, which have to be filtered before any furthermore hydrologic use. There is a very good consistency between the two types of analysis. This agreement helps to confirm the cause and extent of sources of error in the real images. These confirm the areas within the urban area affected by the phenomena of ground clutter. The list of these pixels considered less reliable, has been compiled and they were screened to very locally compare the radar values to the values of rainfall in the urban community of Lyon. Indeed, Lyon has a network of measuring the rain in urban areas among the densest in Europe, totaling about fifty rainfall stations of various organizations on its territory, which creates a density of about one rain gauge for sixteen km. In this study, only raingauges properties of the Urban Community of Lyon were used: 29 tipping bucket devices currently in operation, providing data each 6 minutes. The average rain radar on the town were calculated for the sample of 17 rain episodes from the period 2001 - 2005, and compared to average from 29 rain gauges Grand Lyon. The differences between radar estimations and rainfall values show high amplitude over time, especially in winter. Thus, a factor based on raingauges was assigned to radar data in order to match the average values and radar rainfall for each rain events. These radar adjusted data were then compared to each punctual rainfall values associated (each raingauge value has been compared to a radar pixel value associated thanks to a vertical extraction). The comparison of surface and punctual radar data to the values of the dense network of rain gauges in the community showed a small difference between these measurement values after the use of a spatial uniform weighting ratio, and filtering pixels of lower quality. Specifically, the average difference between radar data and rainfall values around 20% episodes all together, but drops to nearly 10% during exceptionally abundant or long term time rainy episodes potentially harmful. To provide complete coverage of data on the study territory, especially on ground clutter zones filtered, two spatialization techniques were used. The results of the cross validation have shown the usefulness of ordinary kriging compared to cokriging, which is a lot more complicated to use and not really better in this precise study case.

  20. Space-time modeling of a rainfall field ; Application to daily rainfall in the Loire basin

    NASA Astrophysics Data System (ADS)

    Lepioufle, Jean-Marie; Leblois, Etienne; Creutin, Jean-Dominique

    2010-05-01

    Water resources management for a watershed necessitates to assess both high flow volumes and the impact of the management practice for different stakeholders (hydropower, irrigation, ecology...). To test different management strategies, hydrologists have developed hydrological distributed models incorporating several computational objects such as digital elevation model, sub-basins, and distances to the basin outlet. A good characterization of rainfall variability in space and time is crucial for the relevance of a hydrological model as a basis for the choice of water management strategy. Climatological references of rainfall hazard must be built from observation over decades. Daily rainfall measurements from raingauge networks are therefore still an invaluable source of information for a precise representation of precipitation hazard despite the recent availability of radar estimates. Based on either raingauge or radar observations, it is possible to mathematically model rainfall field as a space-time intermittent process (superposition of inner variability field and rainfall indicator field, both influenced by advection). Geostatistics enables to investigate the link between an instantaneous process space-time structure and the evolution of spatial structure with time aggregation.. A method is proposed to infer a relevant instantaneous process from observed rainfall statistics. After fitting the parameters of the instantaneous space-time variogram with the simplex method, spatial variograms for different duration respecting time aggregated variograms is calculated. With this basis, an avenue is open to simulate homogeneous rainfall fields which respect major statistical characteristics for hydrologists: expectation and variance of rainfall distribution and spatial variogram for different durations. Benefits and limits of this approach are investigated using daily rainfall data from the Loire basin in France. Two sub-regions are highlighted. A downstream zone where a quite homogeneous rainfall process can be modeled by the space-time model, and an upstream zone where interaction with orography is more present and the homogeneity assumption questionable. Statistical characteristics of rainfall vary also according to the season and to the atmospheric circulation pattern. An easy way to take into account this variability is the use of a weather type classification as the one presented by Paquet et al (2006). Each day of the precipitation measurement time series is described by one of the eight types. Parameter set of an instantaneous space-time process is estimated for each weather type so that rainfall field might be simulated relative to each weather type. Suggestions are given to take into account spatial and temporal heterogeneity so that an operational space-time model of daily rainfall on the Loire basin can be achieved.

  1. Shuttle imaging radar-B (SIR-B) data analysis for identifying rainfall event occurrence and intensity

    NASA Technical Reports Server (NTRS)

    1985-01-01

    The utility of SIR-B data were evaluated for the detection and measurement of rainfall events, and applications of SIR-B data were developed to the improvement of existing rainfall models. During the SIR-B mission, EarthSat monitored rainfall events occurring within the conterminous United States. The GOES scenes form showed rainfall activity within the conterminous U.S. during the SIR-B mission. Swaths of the actual SIR-B data taken were plotted onto the GOES satellite scenes most closely representing the time of the Shuttle overpass. The JPL provided EarthSat with available SIR-B imagery in paper print form representing the appropriate requested data takes. EarthSat identified the collateral data required for site characterization during subsequent SIR-B contracts with JPL.

  2. Validating NEXRAD MPE and Stage III precipitation products for uniform rainfall on the Upper Guadalupe River Basin of the Texas Hill Country

    NASA Astrophysics Data System (ADS)

    Wang, Xianwei; Xie, Hongjie; Sharif, Hatim; Zeitler, Jon

    2008-01-01

    SummaryThis study examines the performance of the Next Generation Weather Radar (NEXRAD) Multisensor Precipitation Estimator (MPE) and Stage III precipitation products, using a high-density rain gauge network located on the Upper Guadalupe River Basin of the Texas Hill Country. As point-area representativeness error of gauge rainfall is a major concern in assessment of radar rainfall estimation, this study develops a new method to automatically select uniform rainfall events based on coefficient of variation criterion of 3 by 3 radar cells. Only gauge observations of those uniform rainfall events are used as ground truth to evaluate radar rainfall estimation. This study proposes a new parameter probability of rain detection (POD) instead of the conditional probability of rain detection (CPOD) commonly used in previous studies to assess the capability that a radar or gauge detects rainfall. Results suggest that: (1) gauge observations of uniform rainfall better represent ground truth of a 4 × 4 km 2 radar cell than non-uniform rainfall; (2) the MPE has higher capability of rain detection than either gauge-only or Stage III; (3) the MPE has much higher linear correlation and lower mean relative difference with gauge measurements than the Stage III does; (4) the Stage III tends to overestimate precipitation (20%), but the MPE tends to underestimate (7%).

  3. Designing clutter rejection filters with complex coefficients for airborne pulsed Doppler weather radar

    NASA Technical Reports Server (NTRS)

    Jamora, Dennis A.

    1993-01-01

    Ground clutter interference is a major problem for airborne pulse Doppler radar operating at low altitudes in a look-down mode. With Doppler zero set at the aircraft ground speed, ground clutter rejection filtering is typically accomplished using a high-pass filter with real valued coefficients and a stopband notch centered at zero Doppler. Clutter spectra from the NASA Wind Shear Flight Experiments of l991-1992 show that the dominant clutter mode can be located away from zero Doppler, particularly at short ranges dominated by sidelobe returns. Use of digital notch filters with complex valued coefficients so that the stopband notch can be located at any Doppler frequency is investigated. Several clutter mode tracking algorithms are considered to estimate the Doppler frequency location of the dominant clutter mode. From the examination of night data, when a dominant clutter mode away from zero Doppler is present, complex filtering is able to significantly increase clutter rejection over use of a notch filter centered at zero Doppler.

  4. Use of radar rainfall estimates and forecasts to prevent flash flood in real time by using a road inundation warning system

    NASA Astrophysics Data System (ADS)

    Versini, Pierre-Antoine

    2012-01-01

    SummaryImportant damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions, representing major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods, and an application devoted to the road network has also been recently developed for the North part of this region. This warning system combines distributed hydro-meteorological modelling and susceptibility analysis to provide warnings of road inundations. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, around 200 mm dropped on the South part of the Gard and many roads were submerged. Radar-based QPE and QPF have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. Used on an area it has not been calibrated, the results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall forecasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding 1 h.

  5. Second-order multiple-scattering theory associated with backscattering enhancement for a millimeter wavelength weather radar with a finite beam width

    NASA Technical Reports Server (NTRS)

    Kobayashi, Satoru; Tanelli, Simone; Im, Eastwood

    2005-01-01

    Effects of multiple scattering on reflectivity are studied for millimeter wavelength weather radars. A time-independent vector theory, including up to second-order scattering, is derived for a single layer of hydrometeors of a uniform density and a uniform diameter. In this theory, spherical waves with a Gaussian antenna pattern are used to calculate ladder and cross terms in the analytical scattering theory. The former terms represent the conventional multiple scattering, while the latter terms cause backscattering enhancement in both the copolarized and cross-polarized components. As the optical thickness of the hydrometeor layer increases, the differences from the conventional plane wave theory become more significant, and essentially, the reflectivity of multiple scattering depends on the ratio of mean free path to radar footprint radius. These results must be taken into account when analyzing radar reflectivity for use in remote sensing.

  6. Airborne derivation of microburst alerts from ground-based Terminal Doppler Weather Radar information: A flight evaluation

    NASA Technical Reports Server (NTRS)

    Hinton, David A.

    1993-01-01

    An element of the NASA/FAA windshear program is the integration of ground-based microburst information on the flight deck, to support airborne windshear alerting and microburst avoidance. NASA conducted a windshear flight test program in the summer of 1991 during which airborne processing of Terminal Doppler Weather Radar (TDWR) data was used to derive microburst alerts. Microburst information was extracted from TDWR, transmitted to a NASA Boeing 737 in flight via data link, and processed to estimate the windshear hazard level (F-factor) that would be experienced by the aircraft in each microburst. The microburst location and F-factor were used to derive a situation display and alerts. The situation display was successfully used to maneuver the aircraft for microburst penetrations, during which atmospheric 'truth' measurements were made. A total of 19 penetrations were made of TDWR-reported microburst locations, resulting in 18 airborne microburst alerts from the TDWR data and two microburst alerts from the airborne reactive windshear detection system. The primary factors affecting alerting performance were spatial offset of the flight path from the region of strongest shear, differences in TDWR measurement altitude and airplane penetration altitude, and variations in microburst outflow profiles. Predicted and measured F-factors agreed well in penetrations near microburst cores. Although improvements in airborne and ground processing of the TDWR measurements would be required to support an airborne executive-level alerting protocol, the practicality of airborne utilization of TDWR data link data has been demonstrated.

  7. Ground validation of Dual Precipitation Radar (DPR) on GPM by rapid scan Phased Array weahter Radar (PAR)

    NASA Astrophysics Data System (ADS)

    Hirano, Y.; Mega, T.; Shimamura, S.; Wu, T.; Kikuchi, H.; Ushio, T.; Yoshikawa, E.; Chandra, C. V.

    2014-12-01

    The core observatory satellite of the Global Precipitation Measurement (GPM) mission was launched on February 27th 2014. The Dual-frequency Precipitation Radar (DPR) on the GPM core observatory is the succession of the TRMM Precipitation Radar (PR). The DPR consists of a Ku-band precipitation radar and a Ka-band precipitation radar. The DPR is expected to be more sensitive than the PR especially in the measurement of light rainfall and snowfall in high latitude regions. Because of the difference of spatial and temporal resolutions, Space Radar (SR) and conventional type of Ground Radar (GR) are hard to compare.The SR observes each point of earth in short time, for example one footprint is an observation in some microseconds. Rain-gauge measurements have accurate rainfall rate, but rain-gage observes small area and accumulated rainfall in some minutes. The conventional GR can cover a wide area, however, a volume scan requires several minutes. The Phased Array weather Radar (PAR) is developed by Osaka University, Toshiba, and NICT. The PAR is a weather-radar on X-band within 100m range sampling. High spatial and temporal resolution is achieved by the PAR with pulse compression and the digital beam-forming technique. The PAR transmits a wide beam and receives narrow beams by using digital beam forming. Then, the PAR observes many elevation angles from a single pulse. The time of each volume scan is 10-30 seconds in operation, typically 30 seconds. The study shows comparisons between the DPR and the PAR by more similar spatial and temporal resolution. The rainfall region of DPR is similar to the one of PAR. Correlation coefficient of both radar reflectivity suggests more than 0.8 in the 20km range of PAR. As a result, it is considered that DPR can observe with high accuracy. We present the case study which DPR overpassed the PAR observation region in detail.

  8. High resolution rainfall data for urban hydrology, flood modelling and prediction

    NASA Astrophysics Data System (ADS)

    ten Veldhuis, J. A. E.; Maksimovic, C.; Schertzer, D.; Willems, P.

    2012-04-01

    Hydrological analysis of urban catchments requires high resolution rainfall and catchment information because of the small size of these catchments, their fast runoff processes and related short response times. Over the last three decades, analysis of the performance of urban drainage systems has been done mainly through hydrodynamic model simulations. Rainfall input into these models has often been restricted to a single or a few rain gauge(s) in or near the catchment, rendering rainfall input into 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 is becoming increasingly available. Still, the scale of available radar rainfall information, with pixels of 1 to 2.5 km2, does no not meet the relevant scales of urban hydrology (e.g. Berne et al. 2004; Emmanuel et al., 2011). In addition, studies comparing rainfall data from radar and rain gauges show a deviation of 10 to even 50%, with larger differences for increasing temporal and spatial resolutions (e.g. Overeem and Holleman, 2010). A new type of high resolution (X-band) weather radars promises to provide more accurate rainfall estimates at the spatial and temporal scales that are required for urban hydrological analysis (Willems et al., 2012). Recently, the RAINGAIN project was started to analyse the applicability of this new type of radars in the context of urban hydrological modelling. In this project, rainfall data from C-band and X-band radars and a network of rain gauges will be analysed in four highly urbanised catchments: Leuven (Belgium), two boroughs of London (UK), two catchments in Paris (France) and two polder catchments in Rotterdam (the Netherlands). High resolution rainfall data will be used as input into high resolution urban hydrological and hydrodynamic models to simulate and predict urban flood flooding using hybrid 1D-2D approaches (Simões et al., 2010). Details of the radar equipments, characteristics of the four urban catchments and hydrological and hydrodynamic simulation models will be provided; results of the project stage and of a specialist workshop on radar rainfall estimation will be reported.

  9. Flash flood prediction using an un-calibrated hydrological model and radar rainfall data in a Mediterranean watershed under changing hydrological conditions

    NASA Astrophysics Data System (ADS)

    Rozalis, Shahar; Morin, Efrat; Yair, Yoav; Price, Colin

    2010-05-01

    Flash floods are one of the most severe natural disasters in Europe in general and in Mediterranean areas in particular. They can cause severe damage to property, infrastructures and loss of human life. The complexity of flash-flood generation processes and their dependency on different factors related to watershed properties and rainfall characteristics make flash flood prediction a difficult task. In this study, as a part of the EU-FLASH project, we use an un-calibrated hydrological model to simulate flow events in a 27 km2 Mediterranean watershed in Israel and to analyze and better understand the various factors affecting them. The model is based on the well-known SCS Curve Number method for rainfall-runoff calculations and on the kinematic wave method for flow routing. Existing data available from maps, GIS and field studies have been used to define model parameters, and no further calibration has been conducted to get a better fit between computed and observed flow data. The model rainfall input was obtained from the high temporal and spatial resolution radar data adjusted to rain gauges. 20 flow events which occurred within the study area along a 15 years period have all been analyzed. The model shows a generally good prediction capability (e.g., r2=0.7 for peak discharge) which is mainly due to the high performance in predicting flash-floods generated by intense, short-lived convective storm events (r2=0.9). A better performance is achieved when considering the flood level; then the model is able to predict all events defined as high level flood events. The degree of urban development was found to have a large effect on runoff amount and peak discharge with higher sensitivity of moderate and low flow events relative to high flows. Flash-flood generation was also found to be very sensitive to the temporal distribution of rain intensity within the specific storm event.

  10. Monitoring of the plume from the basaltic phreatomagmatic 2004 Grímsvötn eruption—application of weather radar and comparison with plume models

    NASA Astrophysics Data System (ADS)

    Oddsson, Björn; Gudmundsson, Magnús T.; Larsen, Guðrún; Karlsdóttir, Sigrún

    2012-08-01

    The Grímsvötn eruption in November 2004 belongs to a class of small- to medium-sized phreatomagmatic eruptions which are common in Iceland. The eruption lasted 6 days, but the main phase, producing most of the 0.02 km3 of magma erupted, was visible for 33 h on the C-band weather radar of the Icelandic Meteorological Office located in Keflavík, 260 km to the west of the volcano. The plume rose to 8-12 km high over sea level during 33 h. The long distance between radar and source severely reduces the accuracy of the plume height determinations, causing 3.5-km steps in recorded heights. Moreover, an apparent height overestimate of ~1.5 km in the uncorrected radar records occurs, possibly caused by wave ducting or super-refraction in the atmosphere. The stepping and the height overestimate can be partly overcome by averaging the plume heights and by applying a height adjustment based on direct aircraft measurements. Adjusted weather radar data on plume height are used to estimate the total mass erupted using empirical plume models mostly based on magmatic eruptions and to compare it with detailed in situ measurements of the mass of erupted tephra. The errors arising because of the large radar plume distance limit the applicability of the data for detailed comparisons. However, the results indicate that the models overestimate the mass erupted by a factor of three to four. This supports theoretical models indicating that high steam content of phreatomagmatic (wet) plumes enhances their height compared to dry plumes.

  11. Path-Integrated Attenuation from Airborne X-Band Radar and Passive Radiometer Measurements: Implication for Rainfall Measurements

    NASA Technical Reports Server (NTRS)

    Tian, Lin; Heymsfield, Gerry; Weinman, Jim; Starr, David OC. (Technical Monitor)

    2002-01-01

    This study compares path-integrated attenuation (PIA), in precipitation over the ocean, derived from a single-frequency X-band radar, using the surface reference technique (SRT), with that deduced from a radiometer also operating at X band. The data were collected during TRMM field campaigns. The PIA derived from radar using the SRT does not involve any assumptions regarding the precipitation but it assumes that the cross-section of the surface is stable, that is, it is not significantly altered by factors such as surface roughness. The PIA deduced from the radiometer, however, involves assumptions regarding the temperature and emissivity of the surface and absorption and scattering by the intervening precipitation, which in turn depend upon the size, concentration and composition of the precipitation particles. The comparison of the PIA from the two instruments serves not only as a check between the radar and the radiometer but also may yield insights into the structure of the intervening precipitation. Such study can provide valuable information for TRMM in which both radar and radiometers are used for rain measurements. The radiometer PIA was first deduced from the brightness temperature using a simple one-layer radiative transfer model assuming no scattering, an isothermal atmosphere. The initial results show a general agreement between the PIAs deduced from the two instruments. Largo disagreement was found at high values of PIAs that may have been caused saturation of the X-band brightness temperature or by uncertainties in wind roughening of the sea surface that affects the SRT. Further results including the effects of scattering and a non-isothermal atmosphere will be shown at the conference.

  12. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.

  13. Comparison of Spatial and Temporal Rainfall Characteristics in WRF-Simulated Precipitation to Gauge and Radar Observations

    EPA Science Inventory

    Weather Research and Forecasting (WRF) meteorological data are used for USEPA multimedia air and water quality modeling applications, within the CMAQ modeling system to estimate wet deposition and to evaluate future climate and land-use scenarios. While it is not expected that hi...

  14. Spatio-Temporal Description of the Rainfall for Colombian Andean Mountainous Region for Weather Forecasting Purposes. Case Study: Manizales - Caldas, Colombia

    NASA Astrophysics Data System (ADS)

    Suarez Hincapie, J. N.

    2014-12-01

    Manizales is a city located in west-central Colombian Andes in the Caldas province, whose spatial location coincides with one of the most threatened areas of Colombia (landslides, earthquakes, volcanic eruptions, other). As a middle Andean mountainous city and for being located in the area of influence of the ITCZ presents an equatorial mountain climate with a bimodal rainfall regime, and with an average annual rainfall around 2000 mm, it shows very significant rates of precipitation, on average, 70% of the days of the year it is rainy. This situation favors the formation of large masses of clouds and the presence of macroclimatic phenomena such as ENSO, which has historically caused large-scale impacts in both warm and cold phase. Since last decade different entities have implemented a hydro-meteorological network which measures and transmits telemetrically every five minutes hydro-climatic variables. In general, the real-time weather monitoring should be used for a better understanding of our environmental urban environment and to establish indicators of quality of life and welfare for the community. Despite the city has telemetric data on atmospheric and hydrological variables, there is still no tool or a methodology able to generate a spatio-temporal description of these variables. So, the aim of this work is to establish guidelines to sort all this information of atmospheric variables monitored in real time with the help of data mining techniques, machine learning tools to improve the knowledge of atmospheric patterns at Manizales and to serve for territorial planning and decision makers. To reach this purpose the current data warehouse available at the National University of Colombia at Manizales will be used, and it will be fed with observed variables from hydro-meteorological monitoring stations that transmit in real-time. Then, as mentioned this information will make the corresponding processing with data mining techniques to describe the rainfall patterns. All this complemented with the application of statistical techniques for data analysis and exploration. The main contribution of this research is the creation of tools to be used in numerical modeling with forecasting purposes, aiming to improve the resolution given by mesoscale models, which are currently used for weather forecast in Colombia.

  15. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2015-04-01

    Accurate measurements of rainfall are important in many hydrological applications, for instance, flash-flood early-warning systems, hydraulic structures design, agriculture, weather forecasting, and climate modelling. Rainfall intensities can be retrieved from (commercial) microwave link networks. Whenever possible, link networks measure and store the decrease in power of the electromagnetic signal at regular intervals. The decrease in power is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the physics involved in the measurements such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology, the spatial density of the network, and the availability of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of The Netherlands. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also to test the actual and optimal performance of one commercial microwave network from one of the cellular providers in The Netherlands.

  16. Linking the Annual Variation of Snow Radar-derived Accumulation in West Antarctica to Long-term Automatic Weather Station Measurements

    NASA Astrophysics Data System (ADS)

    Feng, B.; Braaten, D. A.; Gogineni, P.; Paden, J. D.; Leuschen, C.; Purdon, K.

    2013-12-01

    Understanding the snow accumulation rate on polar ice sheets is important in assessing mass balance and ice sheet contribution to sea level rise. Measuring annual accumulation on a regional scale and extending back in time several decades has been accomplished using the Center for Remote Sensing of Ice Sheets (CReSIS) Snow Radar on the NASA DC-8 that is part of NASA's Ice-Bridge project. The Snow Radar detects and maps near-surface internal layers in polar firn, operating from 2- 6 GHz and providing a depth resolution of ~4 cm. During November 2011, Snow Radar data were obtained for large areas of West Antarctica, including a flight segment that passed within ~70 km of Byrd Station (80°S, 119°W). Byrd Station has a very long automatic weather station (AWS) record, extending from present to 1980, with 3 relatively brief gaps in the record. The AWS data for Byrd Station were obtained from the Antarctic Meteorological Research Center (AMRC) at the University of Wisconsin. The L1B Snow Radar data products, available from the National Snow and Ice Data Center (NSIDC), were analyzed using layer picking software to obtain the depth of reflectors in the firn that are detected by the radar. These reflectors correspond to annual markers in the firn, and allow annual accumulation to be determined. Using the distance between the reflectors and available density profiles from ice cores, water equivalent accumulation for each annual layer back to 1980 is obtained. We are analyzing spatial variations of accumulation along flight lines, as well as variations in the time series of annual accumulation. We are also analyzing links between annual accumulation and surface weather observations from the Byrd Station AWS. Our analyses of surface weather observations have focused on annual temperature, atmospheric pressure and wind extremes (e.g. 5th and 95th percentiles) and links to annual snow accumulation. We are also examining satellite-derived sea ice extent records for the Bellingshausen and Amundsen seas sector (60°W-120°W) over the same 31-year time period and comparing results to annual snow accumulation. Results from this work will be presented at the meeting.

  17. The Waves to Weather Challenge: Do Large-Scale Equatorial Waves Modulate Regional Rainfall in Southern Vietnam?

    NASA Astrophysics Data System (ADS)

    Fink, A. H.; van der Linden, R.; Phan-Van, T.; Pinto, J. G.

    2014-12-01

    About 85% of the annual precipitation in southern Vietnam (ca. 8-12°N, 104-110°E) occurs during the southwest monsoon season (June to October). Large-scale equatorial waves like the Madden-Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEWs) are known to modulate the large-scale convective activity, often indicated by variations in (filtered) satellite-observed outgoing longwave radiation (OLR) anomalies. The present contribution analyses and quantifies the role of the MJO and CCEWs for rainfall not only in southern and central Vietnam as a whole, but also for smaller climatological sub-regions. Using circum-equatorial NOAA OLR (15°S-15°N), prominent spectral peaks are identified in wavenumber-frequency diagrams along the dispersion curves for the solutions of the shallow water equations. They are interpreted as CCEWs. Meridionally averaged wave-filtered OLR and its time derivatives are used to define phases and amplitudes of CCEWs. This will allow determining active and inactive phases of CCEWs in the vicinity of Vietnam. Eastward propagating deep convection is also related to the 30-90-day MJO. The OLR MJO Index (OMI) is used for the definition of convectively active and inactive phases of the MJO. TRMM 3B42 V7, APHRODITE MA V1101 data, and rain gauge measurements are used to investigate the relation between tropical wave phases and amplitudes and precipitation in southern and central Vietnam and adjacent regions. Results using the OMI are compared with those using the Real-time Multivariate MJO (RMM) Index. The major findings are: (a) Precipitation amounts in southern Vietnam are higher during convectively active phases of the MJO and CCEWs. The waves differ in terms of their relative importance for rainfall enhancement. (b) For increasing CCEW amplitudes, the difference between area-averaged precipitation during inactive and active phases increases. We provide evidence that precipitation amounts are higher when multiple wave types are in their convectively active phases over the Vietnam region.

  18. Terminal doppler weather radar (TDWR) build 5B operational test and evaluation (OT&E) integration and OT&E operational test plan

    NASA Astrophysics Data System (ADS)

    Martinez, Radame; Viveiros, Steven; Wedge, Donne; Guthlein, Peter

    1995-03-01

    The Terminal Doppler Weather Radar (TDWR) Build 5B Enhancement Operational Test and Evaluation (OT&E) Integration and OT&E Operational Test Plan provides the overall philosophy and approach to Build 5B OT&E testing, and identifies OT&E objectives, responsibilities, and resources. The TDWR Build 5B Enhancement provides connectivity to the Low Level Wind Shear Alert System (LLWAS) III to display LLWAS III data along with TDWR hazardous weather data on TDWR Geographic Situation Displays (GSD) and Ribbon Display Terminals (RDT). The TDWR Build 5B OT&E is scheduled to occur at the TDWR sites in Denver, CO, November and December 1994, and in Orlando, FL, spring 1995.

  19. Cloud and Precipitation Radar

    NASA Astrophysics Data System (ADS)

    Hagen, Martin; Höller, Hartmut; Schmidt, Kersten

    Precipitation or weather radar is an essential tool for research, diagnosis, and nowcasting of precipitation events like fronts or thunderstorms. Only with weather radar is it possible to gain insights into the three-dimensional structure of thunderstorms and to investigate processes like hail formation or tornado genesis. A number of different radar products are available to analyze the structure, dynamics and microphysics of precipitation systems. Cloud radars use short wavelengths to enable detection of small ice particles or cloud droplets. Their applications differ from weather radar as they are mostly orientated vertically, where different retrieval techniques can be applied.

  20. Correction of Sampling Errors in Ocean Surface Cross-Sectional Estimates from Nadir-Looking Weather Radar

    NASA Technical Reports Server (NTRS)

    Caylor, I. Jeff; Meneghini, R.; Miller, L. S.; Heymsfield, G. M.

    1997-01-01

    The return from the ocean surface has a number of uses for airborne meteorological radar. The normalized surface cross section has been used for radar system calibration, estimation of surface winds, and in algorithms for estimating the path-integrated attenuation in rain. However, meteorological radars are normally optimized for observation of distributed targets that fill the resolution volume, and so a point target such as the surface can be poorly sampled, particularly at near-nadir look angles. Sampling the nadir surface return at an insufficient rate results in a negative bias of the estimated cross section. This error is found to be as large as 4 dB using observations from a high-altitude airborne radar. An algorithm for mitigating the error is developed that is based upon the shape of the surface echo and uses the returned signal at the three range gates nearest the peak surface echo.

  1. Sources of uncertainty in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-03-01

    Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received power of the electromagnetic signal at regular intervals. The decrease in power can be converted to rainfall intensity, and is largely due to the attenuation by raindrops along the link paths. Such alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the errors involved in single-link rainfall retrievals such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, quantization of the received power, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology and the spatial density of link measurements. We computed ~3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of the Netherlands. Simulated link rainfall depths were obtained from radar data. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also to test the actual and optimal performance of one commercial microwave network from one of the cellular providers in the Netherlands.

  2. Countrywide rainfall maps from a commercial cellular telecommunication network

    NASA Astrophysics Data System (ADS)

    Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2012-12-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information. Many countries do not have continuously operating weather radars, and have no or few rain gauges. A new development is rainfall estimation from microwave links of commercial cellular telecommunication networks. Such networks cover large parts of the land surface of the earth and have a high density, especially in urban areas. The estimation of rainfall using commercial microwave links could therefore become a valuable source of information. The data produced by microwave links is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (1500) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both calibration and validation are done using gauge-adjusted radar data. Validation results reveal that relatively accurate country-wide rainfall maps can be obtained from microwave link data. Since cellular telephone networks are used worldwide, data from such networks could also be used to obtain rainfall maps over larger areas and in areas where no other sources of rainfall data are available.

  3. Dissolved rainfall inputs and streamwater outputs in an undisturbed watershed on highly weathered soils in the Brazilian cerrado

    NASA Astrophysics Data System (ADS)

    Markewitz, Daniel; Resende, Julio C. F.; Parron, Lucilia; Bustamante, Mercedes; Klink, Carlos A.; Figueiredo, Ricardo De O.; Davidson, Eric A.

    2006-08-01

    The cerrados of Brazil cover 2 million km2. Despite the extent of these seasonally dry ecosystems, little watershed research has been focused in this region, particularly relative to the watersheds of the Amazon Basin. The cerrado shares pedogenic characteristics with the Amazon Basin in draining portions of the Brazilian shield and in possessing Oxisols over much of the landscape. The objective of this research was to quantify the stream water geochemical relationships of an undisturbed 1200 ha cerrado watershed for comparison to river geochemistry in the Amazon. Furthermore, this undisturbed watershed was used to evaluate stream discharge versus dissolved ion concentration relationships. This research was conducted in the Córrego Roncador watershed of the Reserva Ecológica do Roncador (RECOR) of the Instituto Brasileiro Geografia e Estatística (IBGE) near Brasilia, Brazil. Bulk precipitation and stream water chemistry were analysed between May 1998 and May 2000. The upland soils of this watershed are nutrient poor possessing total stocks of exchangeable elements in the upper 1 m of 81 +/- 13, 77 +/- 4, 25 +/- 3, and 1 +/- 1 kg ha-1 of K, Ca, Mg, and P, respectively. Bulk precipitation inputs of dissolved nutrients for this watershed are low and consistent with previous estimates. The nutrient-poor soils of this watershed, however, increase the relative importance of precipitation for nutrient replenishment to vegetation during episodes of ecosystem disturbance. Stream water dissolved loads were extremely dilute with conductivities ranging from 4 to 10 μS cm-1 during periods of high- and low-flow, respectively. Despite the low concentrations in this stream, geochemical relationships were similar to other Amazonian streams draining shield geologies. Discharge-concentration relationships for Ca and Mg in these highly weathered soils developed from igneous rocks of the Brazilian shield demonstrated a significant negative relationship indicating a continued predominance of groundwater baseflow contributions these cationic elements.

  4. The effectiveness of adaptive PRF (Pulse Repetition Frequency) selection in minimizing range obscuration in the TDWR (Terminal Doppler Weather Radar) system

    NASA Astrophysics Data System (ADS)

    Crocker, S. C.

    1989-07-01

    An adaptive procedure for selecting radar pulse repetition frequency (PRF) has been developed as the primary means of minimizing the occurrence of range aliased echoes within operationally significant coverage areas (e.g., airport runways) of the Terminal Doppler Weather Radar (TDWR) system. This procedure underwent extensive testing at the S-Band TDWR testbed while located in Denver, CO, where it was judged to be highly successful at preserving the integrity of data collected within the vicinity of the Stapleton International Airport runways. The actual TDWR system will operate at a C-Band frequency, and an increase in potential range obscuration is expected over that experienced by the S-band testbed. This report discusses the anticipated performance of the PRF selection procedure in the C-Band environment by extrapolating results obtained using S-Band testbed data. The results conclusively demonstrates the efficacy of adaptive PRF selection as a method by which to reduce potential range obscuration. A worst-case scenario, for example, indicates that over 20 percent of the TDWR radar data collected about the airport runways has the potential for being contaminated with range aliased echoes at any given time during TDWR surveillance operations. With adaptive PRF selection, however, the expected obscuration is reduced to only 3 percent.

  5. Urban Flood Warning Systems using Radar Technologies

    NASA Astrophysics Data System (ADS)

    Fang, N.; Bedient, P. B.

    2013-12-01

    There have been an increasing number of urban areas that rely on weather radars to provide accurate precipitation information for flood warning purposes. As non-structural tools, radar-based flood warning systems can provide accurate and timely warnings to the public and private entities in urban areas that are prone to flash floods. The wider spatial and temporal coverage from radar increases flood warning lead-time when compared to rain and stream gages alone. The Third Generation Rice and Texas Medical Center (TMC) Flood Alert System (FAS3) has been delivering warning information with 2 to 3 hours of lead time and a R2 value of 93% to facility personnel in a readily understood format for more than 50 events in the past 15 years. The current FAS utilizes NEXRAD Level II radar rainfall data coupled with a real-time hydrologic model (RTHEC-1) to deliver warning information. The system has a user-friendly dashboard to provide rainfall maps, Google Maps based inundation maps, hydrologic predictions, and real-time monitoring at the bayou. This paper will evaluate its reliable performance during the recent events occurring in 2012 and 2013 and the development of a similar radar-based flood warning system for the City of Sugar Land, Texas. Having a significant role in the communication of flood information, FAS marks an important step towards the establishment of an operational and reliable flood warning system for flood-prone urban areas.

  6. Categorisation of northern California rainfall for periods with and without a radar brightband using stable isotopes and a novel automated precipitation collector

    USGS Publications Warehouse

    Coplen, Tyler B.; Paul J. Neiman; Allen B. White; Ralph, F. Martin

    2015-01-01

    During landfall of extratropical cyclones between 2005 and 2011, nearly 1400 precipitation samples were collected at intervals of 30-min time resolution with novel automated collectors at four NOAA sites in northern California [Alta (ATA), Bodega Bay (BBY), Cazadero (CZD) and Shasta Dam (STD)] during 43 events. Substantial decreases were commonly followed hours later by substantial increases in hydrogen isotopic composition (δ2HVSMOW where VSMOW is Vienna Standard Mean Ocean Water) and oxygen isotopic composition (δ18OVSMOW) of precipitation. These variations likely occur as pre-cold frontal precipitation generation transitions from marine vapour masses having low rainout to cold cloud layers having much higher rainout (with concomitant brightband signatures measured by an S-band profiling radar and lower δ2HVSMOW values of precipitation), and finally to shallower, warmer precipitating clouds having lower rainout (with non-brightband signatures and higher δ2HVSMOW values of precipitation), in accord with ‘seeder–feeder’ precipitation. Of 82 intervals identified, a remarkable 100.5 ‰ decrease in δ2HVSMOW value was observed for a 21 January 2010 event at BBY. Of the 61 intervals identified with increases in δ2HVSMOW values as precipitation transitioned to shallower, warmer clouds having substantially less rainout (the feeder part of the seeder–feeder mechanism), a remarkable increase in δ2HVSMOW value of precipitation of 82.3 ‰ was observed for a 10 February 2007 event at CZD. All CZD and ATA events having δ2HVSMOW values of precipitation below −105 ‰ were atmospheric rivers (ARs), and of the 13 events having δ2HVSMOWvalues of precipitation below −80 ‰, 77 % were ARs. Cloud echo-top heights (a proxy for atmospheric temperature) were available for 23 events. The mean echo-top height is greater for higher rainout periods than that for lower rainout periods in 22 of the 23 events. The lowest δ2HVSMOW of precipitation of 28 CZD events was −137.9 ‰ on 16 February 2009 during an AR with cold precipitating clouds and very high rainout with tops >6.5 km altitude. An altitude effect of −2.5 ‰ per 100 m was measured from BBY and CZD δ2HVSMOW data and of −1.8 ‰ per 100 m for CZD and ATA δ2HVSMOW data. We present a new approach to categorise rainfall intervals using δ2HVSMOW values of precipitation and rainfall rates. We term this approach the algorithmic-isotopic categorisation of rainfall, and we were able to identify higher rainout and/or lower rainout periods during all events in this study. We conclude that algorithmic-isotopic categorisation of rainfall can enable users to distinguish between tropospheric vapour masses having relatively high rainout (typically with brightband rain and that commonly are ARs) and vapour masses having lower rainout (commonly with non-brightband rain).

  7. Hydrometeor classification from dual-polarized weather radar: extending fuzzy logic from S-band to C-band data

    NASA Astrophysics Data System (ADS)

    Marzano, F. S.; Scaranari, D.; Celano, M.; Alberoni, P. P.; Vulpiani, G.; Montopoli, M.

    2006-02-01

    A model-based fuzzy classification method for C-band polarimetric radar data, named Fuzzy Radar Algorithm for Hydrometeor Classification at C-band (FRAHCC), is presented. Membership functions are designed for best fitting simulation data at C-band, and they are derived for ten different hydrometeor classes by means of a scattering model, based on T-Matrix numerical method. The fuzzy logic classification technique uses a reduced set of polarimetric observables, i.e. copolar reflectivity and differential reflectivity, and it is finally applied to data coming from radar sites located in Gattatico and S. Pietro Capofiume in North Italy. The final purpose is to show qualitative accuracy improvements with respect to the use of a set of ten bidimensional MBFs, previously adopted and well suited to S-band data but not to C-band data.

  8. Real Time Detection of Anomalies in Streaming Radar and Rain Gauge Data

    NASA Astrophysics Data System (ADS)

    Hill, D. J.; Minsker, B.; Amir, E.; Choi, J.

    2008-12-01

    Radar-rainfall data are being used in an increasing number of real-time applications because of their wide spatial and temporal coverage. Because of uncertainties in radar measurements and the relationship between radar measurements and rainfall on the ground, radar-rainfall data are often combined with rain gauge data to improve their accuracy. While rain gauges can provide accurate estimates of rainfall, their data are sometimes subject to a number of errors caused by the environment in which the gauges are deployed. This study develops a method for automatically detecting anomalies (i.e. data that deviate markedly from historical patterns) in both radar and raingauge data through integration and modeling of data from these two different sources.. These anomalous data can be caused by sensor or data transmission errors or by infrequent system behaviors that may be of interest to the scientific or public safety communities. This study develops an automated anomaly detection method that employs a Dynamic Bayesian Network to assimilate data from multiple rain gauges and weather radar (NEXRAD) into an uncertain model of the current rainfall. Filtering (e.g. Kalman filtering) can then be used to infer the likelihood that a particular gauge measurement is anomalous. Measurements with a high likelihood of being anomalous are classified as such. The method developed in this study performs fast, incremental evaluation of data as they become available; scales to large quantities of data; and requires no a priori information regarding process variables or types of anomalies that may be encountered. The performance of the anomaly detector developed in this study is demonstrated using a precipitation sensor network composed of a NEXRAD weather radar and several near- real-time telemetered rain gauges deployed by the USGS in Chicago. The results indicate that the method performs well at identifying anomalous data caused by a real sensor failure.

  9. Calibration and evaluation of a flood forecasting system: Utility of numerical weather prediction model, data assimilation and satellite-based rainfall

    NASA Astrophysics Data System (ADS)

    Yucel, I.; Onen, A.; Yilmaz, K. K.; Gochis, D. J.

    2015-04-01

    A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. A comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow is then made. The ten rainfall-runoff events that occurred in the Black Sea Region were used for testing and evaluation. With the availability of streamflow data across rainfall-runoff events, the calibration is only performed on the Bartin sub-basin using two events and the calibrated parameters are then transferred to other neighboring three ungauged sub-basins in the study area. The rest of the events from all sub-basins are then used to evaluate the performance of the WRF-Hydro system with the calibrated parameters. Following model calibration, the WRF-Hydro system was capable of skillfully reproducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simulations where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, as compared with surface rain gauges, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were reduced by 22.2% when hydrological model calibration is performed with WRF precipitation. Errors were reduced by 36.9% (above uncalibrated model performance) when both WRF model data assimilation and hydrological model calibration was utilized. Our results also indicated that when assimilated precipitation and model calibration is performed jointly, the calibrated parameters at the gauged sites could be transferred to ungauged neighboring basins where WRF-Hydro reduced mean root mean squared error from 8.31 m3/s to 6.51 m3/s.

  10. Uncertainties on the definition of critical rainfall patterns for debris-flows triggering. Results from the Rebaixader monitoring site (Central Pyrenees)

    NASA Astrophysics Data System (ADS)

    Hürlimann, Marcel; Abancó, Clàudia; Moya, Jose; Berenguer, Marc

    2015-04-01

    Empirical rainfall thresholds are a widespread technique in debris-flow hazard assessment and can be established by statistical analysis of historic data. Typically, data from one or several rain gauges located nearby the affected catchment is used to define the triggering conditions. However, this procedure has been demonstrated not to be accurate enough due to the spatial variability of convective rainstorms. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, 28 torrential flows (debris flows and debris floods) have occurred and rainfall data of 25 of them are available with a 5-minutes frequency of recording ("event rainfalls"). Other 142 rainfalls that did not trigger events ("no event rainfalls) were also collected and analysed. The goal of this work was threefold: a) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential events and others that did not; b) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment; c) estimate the uncertainty derived from the use of rain gauges located outside the catchment based on the spatial correlation depicted by radar rainfall maps. The results of the statistical analysis showed that the parameters that more distinguish between the two populations of rainfalls are the rainfall intensities, the mean rainfall and the total precipitation. On the other side, the storm duration and the antecedent rainfall are not significantly different between "event rainfalls" and "no event rainfalls". Four different ID rainfall thresholds were derived based on the dataset of the first 5 years and tested using the 2014 dataset. The results of the test indicated that the threshold corresponding to the 90% percentile showed the best performance. Weather radar data was used to analyse the spatial variability of the triggering rainfalls. The analysis indicates that rain gauges outside the catchment may be considered useful or not to describe the rainfall depending on the type of rainfall. For widespread rainfalls, further rain gauges can give a reliable measurement, because the spatial correlation decreases slowly with the distance between the rain gauge and the debris-flow initiation area. Contrarily, local storm cells show higher space-time variability and, therefore, representative rainfall measurements are obtained only by the closest rain gauges. In conclusion, the definition of rainfall thresholds is a delicate task. When the rainfall records are coming from gauges that are outside the catchment under consideration, the data should be carefully analysed and crosschecked with radar data (especially for small convective cells).

  11. The study and real-time implementation of attenuation correction for X-band dual-polarization weather radars

    NASA Astrophysics Data System (ADS)

    Liu, Yuxiang

    Attenuation of electromagnetic radiation due to rain or other wet hydrometeors along the propagation path has been studied extensively in the radar meteorology community. Recently, use of short range dual-polarization X-band radar systems has gained momentum due to lower system cost compared with the much more expensive S-band systems. Advances in dual-polarization radar research have shown that the specific attenuation and differential attenuation between horizontal and vertical polarized waves caused by oblate, highly oriented raindrops can be estimated using the specific differential phase. This advance leads to correction of the measured reflectivity (Zh) and the differential reflectivity (Zdr) due to path attenuation. This thesis addresses via theory, simulations and data analyses the accuracy and optimal estimation of attenuation-correction procedures at X-band frequency. Real-time implementation of the correction algorithm was developed for the first generation of X-band dual-polarized Doppler radar network (Integration Project 1, IP1) operated by the NSF Center for Collaborate Adaptive Sensing of the Atmosphere (CASA). We evaluate the algorithm for correcting the Zh, and the Zdr for rain attenuation using simulations and X-band radar data under ideal and noisy situations. Our algorithm is able to adjust the parameters according to the changes in temperature, drop shapes, and a certain class of drop size distributions (DSD) with very fast convergence. The X-band radar data were obtained from the National Institute of Earth Science and Disaster Prevention (NIED), Japan, and from CASA IP1. The algorithm accurately corrects NIED's data when compared with ground truth calculated from in situ disdrometer-based DSD measurements for a Typhoon event. We have implemented, in real-time, the algorithm in all the CASA IP1 radar nodes. We also evaluate our preliminary method that separately estimates rain and wet ice attenuation using microphysical outputs from a previous supercell simulation using the CSU-RAMS (Regional Atmospheric Modeling System). The retrieved rain and wet ice specific attenuation fields were found to be in close correspondence to the 'true' fields calculated from the simulation. The concept to correct rain and wet ice attenuation separately can be also applied to the CASA IP1 network with additional constraint information possibly provided by the WSR-88D network.

  12. Use of Dual Polarization Radar in Validation of Satellite Precipitation Measurements: Rationale and Opportunities

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Hou, Arthur; Smith, Eric; Bringi, V. N.; Rutledge, S. A.; Gorgucci, E.; Petersen, W. A.; SkofronickJackson, Gail

    2008-01-01

    Dual-polarization weather radars have evolved significantly in the last three decades culminating in the operational deployment by the National Weather Service. In addition to operational applications in the weather service, dual-polarization radars have shown significant potential in contributing to the research fields of ground based remote sensing of rainfall microphysics, study of precipitation evolution and hydrometeor classification. Furthermore the dual-polarization radars have also raised the awareness of radar system aspects such as calibration. Microphysical characterization of precipitation and quantitative precipitation estimation are important applications that are critical in the validation of satellite borne precipitation measurements and also serves as a valuable tool in algorithm development. This paper presents the important role played by dual-polarization radar in validating space borne precipitation measurements. Starting from a historical evolution, the various configurations of dual-polarization radar are presented. Examples of raindrop size distribution retrievals and hydrometeor type classification are discussed. The quantitative precipitation estimation is a product of direct relevance to space borne observations. During the TRMM program substantial advancement was made with ground based polarization radars specially collecting unique observations in the tropics which are noted. The scientific accomplishments of relevance to space borne measurements of precipitation are summarized. The potential of dual-polarization radars and opportunities in the era of global precipitation measurement mission is also discussed.

  13. Measurement and interpolation uncertainties in rainfall maps from cellular communication networks

    NASA Astrophysics Data System (ADS)

    Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.

    2015-08-01

    Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received power of the electromagnetic signal at regular intervals. The decrease in power can be converted to rainfall intensity, and is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfils the continuous effort to obtain measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e. the errors involved in link rainfall retrievals, such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, dry weather baseline attenuation, quantization of the received power, drop size distribution (DSD), and multi-path propagation; and (2) those associated with mapping, i.e. the combined effect of the interpolation methodology and the spatial density of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of the Netherlands. Simulated link rainfall depths refer to path-averaged rainfall depths obtained from radar data. The ~ 3500 real and simulated rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also test the actual and optimal performance of one commercial microwave network from one of the cellular providers in the Netherlands. Errors in microwave link measurements were found to be the source that contributes most to the overall uncertainty.

  14. Spaceborne Doppler Precipitation Radar: System Configurations and Performance Analysis

    NASA Technical Reports Server (NTRS)

    Tanelli, Simone; Im, Eastwood

    2004-01-01

    Knowledge of the global distribution of the vertical velocity of precipitation is important in in the study of energy transportation in the atmosphere, the climate and weather. Such knowledge can only be directly acquired with the use of spaceborne Doppler precipitation radars. Although the high relative speed of the radar with respect to the rainfall particles introduces significant broadening in the Doppler spectrum, recent studies have shown that the average vertical velocity can be measured to acceptable accuracy levels by appropriate selection of radar parameters. Furthermore, methods to correct for specific errors arising from NUBF effects and pointing uncertainties have recently been developed. In this paper we will present the results of the trade studies on the performances of a spaceborne Doppler radar with different system parameters configurations.

  15. Sensitivity of hydro-geomorphic processes to catchment-scale variations in rainfall distribution

    NASA Astrophysics Data System (ADS)

    Valters, Declan; Brocklehurst, Simon; Schultz, David

    2015-04-01

    The dynamics of severe storms have a pronounced effect on the temporal and spatial distribution of water input to river catchments in upland environments, particularly those with complex orography and steep topographic gradients. Existing landscape evolution models typically forsake realistic patterns of rainfall during storm events, in favour of uniform rainfall input. It is demonstrated that this simplification fails to resolve localised areas of flooding and erosion within a drainage basin, despite the known significance of erosion thresholds and orographic enhancement of rainfall. This shortfall can be remedied by the incorporation of high-resolution precipitation data from rainfall radar into model simulations, accounting for sub-catchment-scale variation in precipitation patterns. Using a series of simulations with both synthetic and real topographies, it is shown that there is a wide variation in hydro-geomorphic response observed in comparison to simulations with spatially-averaged rainfall: localised water depths and erosion rates vary by up to an order of magnitude within the catchments studied. The real-data examples, chosen from severe UK rainfall events over the last 10 years, are analysed by combining the CAESAR-Lisflood landscape evolution model at 5m resolution with data from the UK Met Office NIMROD rainfall radar at 1km resolution. The model-coupling framework presented is also suited to using output from weather forecasting models. The applications are wide-ranging, from improving the accuracy of hydrological predictions during single storm events, to understanding longer-term evolution of catchment-scale geomorphology.

  16. New software methods in radar ornithology using WSR-88D weather data and potential application to monitoring effects of climate change on bird migration

    USGS Publications Warehouse

    Mead, Reginald; Paxton, John; Sojda, Richard S.

    2010-01-01

    Radar ornithology has provided tools for studying the movement of birds, especially related to migration. Researchers have presented qualitative evidence suggesting that birds, or at least migration events, can be identified using large broad scale radars such as the WSR-88D used in the NEXRAD weather surveillance system. This is potentially a boon for ornithologists because such data cover a large portion of the United States, are constantly being produced, are freely available, and have been archived since the early 1990s. A major obstacle to this research, however, has been that identifying birds in NEXRAD data has required a trained technician to manually inspect a graphically rendered radar sweep. A single site completes one volume scan every five to ten minutes, producing over 52,000 volume scans in one year. This is an immense amount of data, and manual classification is infeasible. We have developed a system that identifies biological echoes using machine learning techniques. This approach begins with training data using scans that have been classified by experts, or uses bird data collected in the field. The data are preprocessed to ensure quality and to emphasize relevant features. A classifier is then trained using this data and cross validation is used to measure performance. We compared neural networks, naive Bayes, and k-nearest neighbor classifiers. Empirical evidence is provided showing that this system can achieve classification accuracies in the 80th to 90th percentile. We propose to apply these methods to studying bird migration phenology and how it is affected by climate variability and change over multiple temporal scales.

  17. Radar remote sensing in biology

    USGS Publications Warehouse

    Moore, Richard K.; Simonett, David S.

    1967-01-01

    The present status of research on discrimination of natural and cultivated vegetation using radar imaging systems is sketched. The value of multiple polarization radar in improved discrimination of vegetation types over monoscopic radars is also documented. Possible future use of multi-frequency, multi-polarization radar systems for all weather agricultural survey is noted.

  18. Doppler radar results

    NASA Technical Reports Server (NTRS)

    Bracalente, Emedio M.

    1992-01-01

    The topics are covered in viewgraph form and include the following: (1) a summary of radar flight data collected; (2) a video of combined aft cockpit, nose camera, and radar hazard displays; (3) a comparison of airborne radar F-factor measurements with in situ and Terminal Doppler Weather Radar (TDWR) F-factors for some sample events; and (4) a summary of wind shear detection performance.

  19. Rainfall Modification by Urban Areas: New Perspectives from TRMM

    NASA Technical Reports Server (NTRS)

    Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew

    2002-01-01

    Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. 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 changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded 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. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.

  20. Use of radar QPE for the derivation of Intensity-Duration-Frequency curves in a range of climatic regimes

    NASA Astrophysics Data System (ADS)

    Marra, Francesco; Morin, Efrat

    2015-12-01

    Intensity-Duration-Frequency (IDF) curves are widely used in flood risk management because they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. Weather radars provide distributed rainfall estimates with high spatial and temporal resolutions and overcome the scarce representativeness of point-based rainfall for regions characterized by large gradients in rainfall climatology. This work explores the use of radar quantitative precipitation estimation (QPE) for the identification of IDF curves over a region with steep climatic transitions (Israel) using a unique radar data record (23 yr) and combined physical and empirical adjustment of the radar data. IDF relationships were derived by fitting a generalized extreme value distribution to the annual maximum series for durations of 20 min, 1 h and 4 h. Arid, semi-arid and Mediterranean climates were explored using 14 study cases. IDF curves derived from the study rain gauges were compared to those derived from radar and from nearby rain gauges characterized by similar climatology, taking into account the uncertainty linked with the fitting technique. Radar annual maxima and IDF curves were generally overestimated but in 70% of the cases (60% for a 100 yr return period), they lay within the rain gauge IDF confidence intervals. Overestimation tended to increase with return period, and this effect was enhanced in arid climates. This was mainly associated with radar estimation uncertainty, even if other effects, such as rain gauge temporal resolution, cannot be neglected. Climatological classification remained meaningful for the analysis of rainfall extremes and radar was able to discern climatology from rainfall frequency analysis.

  1. Spatial and temporal variations in rainfall over Darwin and its vicinity during different large-scale environments

    NASA Astrophysics Data System (ADS)

    Rauniyar, Surendra P.; Walsh, Kevin J. E.

    2016-02-01

    This study analyses the regional variations in rainfall over Darwin and its vicinity due to different large-scale circulations during the Australian summer by utilizing the combination of in situ and C-band polarimetric radar rainfall data at hourly resolution. The eight phases of the Madden-Julian oscillation as defined by Wheeler and Hendon (Mon Weather Rev 132(8):1917-1932, 2004) were used as indicators of different large-scale environments. The analysis found that the large-scale forcing starts to build up from phase 4 by the reversal of low- to mid-level easterly winds to moist westerly winds, reaching a maximum in phase 5 and weakening through phases 6-7. During phases 4-6, most of the study domain experiences widespread rainfall, but with distinct spatial and temporal structures. In addition, during these phases, coastal areas near Darwin receive more rainfall in the early morning (0200-0400 LT) due to the spreading or expansion of rainfall from the Beagle Gulf, explaining the occurrence of a secondary diurnal rainfall peak over Darwin. In contrast, local-scale mechanisms (sea breezes) reinvigorate from phase 8, further strengthening through phases 1-3, when low-level easterly winds become established over Darwin producing rainfall predominately over land and island locations during the afternoon. During these phases, below average rainfall is observed over most of the radar domain, except over the Tiwi Islands in phase 2.

  2. Spatial and temporal variations in rainfall over Darwin and its vicinity during different large-scale environments

    NASA Astrophysics Data System (ADS)

    Rauniyar, Surendra P.; Walsh, Kevin J. E.

    2015-04-01

    This study analyses the regional variations in rainfall over Darwin and its vicinity due to different large-scale circulations during the Australian summer by utilizing the combination of in situ and C-band polarimetric radar rainfall data at hourly resolution. The eight phases of the Madden-Julian oscillation as defined by Wheeler and Hendon (Mon Weather Rev 132(8):1917-1932, 2004) were used as indicators of different large-scale environments. The analysis found that the large-scale forcing starts to build up from phase 4 by the reversal of low- to mid-level easterly winds to moist westerly winds, reaching a maximum in phase 5 and weakening through phases 6-7. During phases 4-6, most of the study domain experiences widespread rainfall, but with distinct spatial and temporal structures. In addition, during these phases, coastal areas near Darwin receive more rainfall in the early morning (0200-0400 LT) due to the spreading or expansion of rainfall from the Beagle Gulf, explaining the occurrence of a secondary diurnal rainfall peak over Darwin. In contrast, local-scale mechanisms (sea breezes) reinvigorate from phase 8, further strengthening through phases 1-3, when low-level easterly winds become established over Darwin producing rainfall predominately over land and island locations during the afternoon. During these phases, below average rainfall is observed over most of the radar domain, except over the Tiwi Islands in phase 2.

  3. On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution

    NASA Astrophysics Data System (ADS)

    Bruni, G.; Reinoso, R.; van de Giesen, N. C.; Clemens, F. H. L. R.; ten Veldhuis, J. A. E.

    2015-02-01

    Cities are increasingly vulnerable to floods generated by intense rainfall, because of urbanisation of flood-prone areas and ongoing urban densification. Accurate information of convective storm characteristics at high spatial and temporal resolution is a crucial input for urban hydrological models to be able to simulate fast runoff processes and enhance flood prediction in cities. In this paper, a detailed study of the sensitivity of urban hydrodynamic response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar were used as input into a detailed hydrodynamic sewer model for an urban catchment in the city of Rotterdam, the Netherlands. The aim was to characterise how the effect of space and time aggregation on rainfall structure affects hydrodynamic modelling of urban catchments, for resolutions ranging from 100 to 2000 m and from 1 to 10 min. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm characteristics and hydrodynamic model properties: rainfall sampling number (rainfall resolution vs. storm size), catchment sampling number (rainfall resolution vs. catchment size), runoff and sewer sampling number (rainfall resolution vs. runoff and sewer model resolution respectively). Results show that for rainfall resolution lower than half the catchment size, rainfall volumes mean and standard deviations decrease as a result of smoothing of rainfall gradients. Moreover, deviations in maximum water depths, from 10 to 30% depending on the storm, occurred for rainfall resolution close to storm size, as a result of rainfall aggregation. Model results also showed that modelled runoff peaks are more sensitive to rainfall resolution than maximum in-sewer water depths as flow routing has a damping effect on in-sewer water level variations. Temporal resolution aggregation of rainfall inputs led to increase in de-correlation lengths and resulted in time shift in modelled flow peaks by several minutes. Sensitivity to temporal resolution of rainfall inputs was low compared to spatial resolution, for the storms analysed in this study.

  4. Comparison of short-term rainfall forecasts for model-based flow prediction in urban drainage systems.

    PubMed

    Thorndahl, Søren; Poulsen, Troels Sander; Bøvith, Thomas; Borup, Morten; Ahm, Malte; Nielsen, Jesper Ellerbæk; Grum, Morten; Rasmussen, Michael R; Gill, Rasphall; Mikkelsen, Peter Steen

    2013-01-01

    Forecast-based flow prediction in drainage systems can be used to implement real-time control of drainage systems. This study compares two different types of rainfall forecast - a radar rainfall extrapolation-based nowcast model and a numerical weather prediction model. The models are applied as input to an urban runoff model predicting the inlet flow to a waste water treatment plant. The modelled flows are auto-calibrated against real-time flow observations in order to certify the best possible forecast. Results show that it is possible to forecast flows with a lead time of 24 h. The best performance of the system is found using the radar nowcast for the short lead times and the weather model for larger lead times. PMID:23863443

  5. Compositing radar reflectivity observations with an inverse method

    NASA Astrophysics Data System (ADS)

    Roca-Sancho, Jordi; Berenguer, Marc; Sempere-Torres, Daniel

    2013-04-01

    Quantitative Precipitation Estimation (QPE) has been one of the main applications of weather radars since its early stages. Nowadays, many advances have improved such estimates and radar networks have been deployed in many countries. In parallel, uncertainty in radar QPE has become a subject of interest by itself because of its significant role in the quality of estimates. When several radars cover the same area, some sources of uncertainty (e.g. path attenuation by intense precipitation, beam blockage or beam broadening), can be dealt using information from the least-affected radars instead of only reproducing a single radar approach in each one. So far, composites of radar observations are carried out through simple criteria (by picking the closest observation, the maximum value…) or quality indices -that need a priori definition of quality descriptors. This study proposes an alternative methodology to retrieve the 3-dimensional reflectivity field most compatible with the measurements from the different radars of the network. With this aim, the methodology uses a model that simulates the radar sampling of the atmosphere. The model settings consider the specific features of each radar such as the location, hardware parameters (frequency, beam width, pulse length…) and scanning strategy. The methodology follows the concept of an inverse method based on the minimization of a cost function that penalizes discrepancies between the simulated and actual observations for each radar of the network. It is worth noting that for radar at attenuating wavelengths, the proposed methodology implicitly corrects the effect of attenuation due to intense rainfall. The methodology has been applied on the network of C-band radars in the vicinity of Barcelona, Spain. The retrievals have been obtained for a 12 hours of rainfall with reflectivity observations of two radars; observations from a third independent radar have been used for verification at different heights. Conventional techniques have been also applied to compare its results with the ones of the proposed method. We analyzed some characteristics such as the vertical structure or the performance in attenuated regions. Different statistics have been computed to quantitatively assess the performance of the different methods; also, the spatial structure of the retrieved fields has been analyzed.

  6. Quantitative precipitation climatology over the Himalayas by using Precipitation Radar on Tropical Rainfall Measuring Mission (TRMM) and a dense network of rain-gauges

    NASA Astrophysics Data System (ADS)

    Yatagai, A.

    2010-09-01

    Quantified grid observation data at a reasonable resolution are indispensable for environmental monitoring as well as for predicting future change of mountain environment. However quantified datasets have not been available for the Himalayan region. Hence we evaluate climatological precipitation data around the Himalayas by using Precipitation Radar (PR) data acquired by the Tropical Rainfall Measuring Mission (TRMM) over 10 years of observation. To validate and adjust these patterns, we used a dense network of rain gauges collected by the Asian PrecipitationHighly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE Water Resources) project (http://www.chikyu.ac.jp/precip/). We used more than 2600 stations which have more than 10-year monthly precipitation over the Himalayan region (75E-105E, 20-36N) including country data of Nepal, Bangladesh, Bhutan, Pakistan, India, Myanmar, and China. The region we studied is so topographically complicated that horizontal patterns are not uniform. Therefore, every path data of PR2A25 (near-surface rain) was averaged in a 0.05-degree grid and a 10-year monthly average was computed (hereafter we call PR). On the other hand, for rain-gauge, we first computed cell averages if each 0.05-degree grid cell has 10 years observation or more. Here we refer to the 0.05-degree rain-gauge climatology data as RG data. On the basis of comparisons between the RG and PR composite values, we defined the parameters of the regressions to correct the monthly climatology value based on the rain gauge observations. Compared with the RG, the PR systematically underestimated precipitation by 28-38% in summer (July-September). Significant correlation between TRMM/PR and rain-gauge data was found for all months, but the correlation is relatively low in winter. The relationship is investigated for different elevation zones, and the PR was found to underestimate RG data in most zones, except for certain zones in February (250-1000m), March (0-1000m), and April (0-1500m). We depicted the adjusted precipitation climatology based on the TRMM/PR composites. The monthly composite patterns of the TRMM/PR for the 10 years show that the southern foothills of the Himalayas always have a clear rain band, with clear dry areas north of the Himalayas. The double rain bands along the Himalayas are clearly shown, and a rain band with a high maximum appeared in the area of Bhutan (around 27N, 90) in summer monsoon season. Little precipitation is observed on the Himalayas or Tibet at elevations higher than 4800 m. In the summer monsoon season, precipitation over the Tibetan Plateau increases, especially in the east. In the winter season (November-March) in particular, more precipitation is seen west of the Himalayas (north India) and very dry areas are observed to the north. Improvement of the APHRODITE's daily grid precipitation analysis by using this climatology will be shown.

  7. Rainfall retrieval in urban areas using commercial microwave links from mobile networks: A modelling feasibility study

    NASA Astrophysics Data System (ADS)

    Zohidov, Bahtiyor; Andrieu, Hervé; Servières, Myriam; Normand, Nicolas

    2014-05-01

    Rainfall is usually measured by networks of rain gauges and weather radars. Many cities worldwide are not supplied with these devices; however, they are generally equipped with mobile telecommunication networks. Mobile networks use atmospheric Hyper-Frequency (HF) links whose transmitted signal power is attenuated by rainfall. Measuring that signal attenuation along each link could allow the measurement of path-averaged rainfall [Leijnse et al 2007, Overeem et al 2013, Messer et al 2006, Guili et al 1991, Zinevich et al 2008, Cuccoli et al 2011]. As HF links are concentrated in cities, these networks could constitute a self-sufficient approach to monitoring rainfall in urban areas. We adopt a simulation approach in order to study the feasibility of mapping rainfall fields at the city scale by means of existing HF links. Our domain of study is the central part of the city of Nantes, France, where the density of cellular networks is greatest. As a basis, we use a data set consisting of hundreds of weather radar images recorded by the Météo-France C band weather radar at high spatial (250m x 250m) and temporal (5 minute) resolutions located about 10 km north of the center of Nantes. We convert these images into rainfall maps using the Z-R relation and consider them as reference rainfall fields. The simulation is performed as follows. First, we simulate the measurement of total attenuation along each HF link using a rain-attenuation model based on Mie theory and a known drop size distribution in a continental temperate climate. This procedure is applied for 256 real radio links operating at different frequencies (18, 23, 38 GHz) with lengths ranging from 0.4 to 16 km. This helps us to substitute the attenuation data for the signal power received from microwave links. Error sources affecting measurement accuracy are introduced as a zero-mean Gaussian distributed random variable with variance of 10% of total attenuation. The retrieval of the rainfield is performed by a nonlinear algorithm [Tarantola and Valette 1982] based on the general nonlinear least square criterion. The a priori knowledge used to initialize the algorithm heavily influences the model outcome if the stated problem is underdetermined. In order to evaluate the performance of our model, we carry out a series of rainfall retrieval tests for various rain events (convective and stratiform) with different time intervals. We evaluate retrieval efficiency by comparing observed rain fields with retrieved ones. We perform a sensitivity analysis to define the model's limitations and capabilities by considering essential factors, namely spatial and temporal rainfall structure, the geometry of HF link networks, the choice of a priori information and associated errors.

  8. Weather Information System

    NASA Technical Reports Server (NTRS)

    1995-01-01

    WxLink is an aviation weather system based on advanced airborne sensors, precise positioning available from the satellite-based Global Positioning System, cockpit graphics and a low-cost datalink. It is a two-way system that uplinks weather information to the aircraft and downlinks automatic pilot reports of weather conditions aloft. Manufactured by ARNAV Systems, Inc., the original technology came from Langley Research Center's cockpit weather information system, CWIN (Cockpit Weather INformation). The system creates radar maps of storms, lightning and reports of surface observations, offering improved safety, better weather monitoring and substantial fuel savings.

  9. Probabilistic rainfall warning system with an interactive user interface

    NASA Astrophysics Data System (ADS)

    Koistinen, Jarmo; Hohti, Harri; Kauhanen, Janne; Kilpinen, Juha; Kurki, Vesa; Lauri, Tuomo; Nurmi, Pertti; Rossi, Pekka; Jokelainen, Miikka; Heinonen, Mari; Fred, Tommi; Moisseev, Dmitri; Mäkelä, Antti

    2013-04-01

    A real time 24/7 automatic alert system is in operational use at the Finnish Meteorological Institute (FMI). It consists of gridded forecasts of the exceedance probabilities of rainfall class thresholds in the continuous lead time range of 1 hour to 5 days. Nowcasting up to six hours applies ensemble member extrapolations of weather radar measurements. With 2.8 GHz processors using 8 threads it takes about 20 seconds to generate 51 radar based ensemble members in a grid of 760 x 1226 points. Nowcasting exploits also lightning density and satellite based pseudo rainfall estimates. The latter ones utilize convective rain rate (CRR) estimate from Meteosat Second Generation. The extrapolation technique applies atmospheric motion vectors (AMV) originally developed for upper wind estimation with satellite images. Exceedance probabilities of four rainfall accumulation categories are computed for the future 1 h and 6 h periods and they are updated every 15 minutes. For longer forecasts exceedance probabilities are calculated for future 6 and 24 h periods during the next 4 days. From approximately 1 hour to 2 days Poor man's Ensemble Prediction System (PEPS) is used applying e.g. the high resolution short range Numerical Weather Prediction models HIRLAM and AROME. The longest forecasts apply EPS data from the European Centre for Medium Range Weather Forecasts (ECMWF). The blending of the ensemble sets from the various forecast sources is performed applying mixing of accumulations with equal exceedance probabilities. The blending system contains a real time adaptive estimator of the predictability of radar based extrapolations. The uncompressed output data are written to file for each member, having total size of 10 GB. Ensemble data from other sources (satellite, lightning, NWP) are converted to the same geometry as the radar data and blended as was explained above. A verification system utilizing telemetering rain gauges has been established. Alert dissemination e.g. for citizens and professional end users applies SMS messages and, in near future, smartphone maps. The present interactive user interface facilitates free selection of alert sites and two warning thresholds (any rain, heavy rain) at any location in Finland. The pilot service was tested by 1000-3000 users during summers 2010 and 2012. As an example of dedicated end-user services gridded exceedance scenarios (of probabilities 5 %, 50 % and 90 %) of hourly rainfall accumulations for the next 3 hours have been utilized as an online input data for the influent model at the Greater Helsinki Wastewater Treatment Plant.

  10. Maximum-likelihood spectral estimation and adaptive filtering techniques with application to airborne Doppler weather radar. Thesis Technical Report No. 20

    NASA Technical Reports Server (NTRS)

    Lai, Jonathan Y.

    1994-01-01

    This dissertation focuses on the signal processing problems associated with the detection of hazardous windshears using airborne Doppler radar when weak weather returns are in the presence of strong clutter returns. In light of the frequent inadequacy of spectral-processing oriented clutter suppression methods, we model a clutter signal as multiple sinusoids plus Gaussian noise, and propose adaptive filtering approaches that better capture the temporal characteristics of the signal process. This idea leads to two research topics in signal processing: (1) signal modeling and parameter estimation, and (2) adaptive filtering in this particular signal environment. A high-resolution, low SNR threshold maximum likelihood (ML) frequency estimation and signal modeling algorithm is devised and proves capable of delineating both the spectral and temporal nature of the clutter return. Furthermore, the Least Mean Square (LMS) -based adaptive filter's performance for the proposed signal model is investigated, and promising simulation results have testified to its potential for clutter rejection leading to more accurate estimation of windspeed thus obtaining a better assessment of the windshear hazard.

  11. Validation of simulated hurricane drop size distributions using polarimetric radar

    NASA Astrophysics Data System (ADS)

    Brown, Bonnie R.; Bell, Michael M.; Frambach, Andrew J.

    2016-01-01

    Recent upgrades to the U.S. radar network now allow for polarimetric measurements of landfalling hurricanes, providing a new data set to validate cloud microphysical parameterizations used in tropical cyclone simulations. Polarimetric radar reflectivity and differential reflectivity simulated by the Weather Research and Forecasting model were compared with real radar observations from 2014 in Hurricanes Arthur and Ana. Six different microphysics parameterizations were tested that were able to capture the major features of both hurricanes, including accurate tracks, precipitation asymmetry, and the approximate intensity of the storms. A high correlation between simulated intensity and rainfall across schemes suggests an intimate link between the latent heating produced by the microphysics and the storm dynamics. Most of the parameterizations produced a higher frequency of larger raindrops than observed. The Thompson aerosol-aware bulk and explicit spectral bin microphysical schemes showed the best fidelity to the observations at a higher computational cost.

  12. Comparison of machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

    NASA Astrophysics Data System (ADS)

    Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

    2015-04-01

    Machine learning (ML) algorithms have been successfully evaluated as valuable tools in satellite-based rainfall retrievals which shows the high potential of ML algorithms when faced with high dimensional and complex data. Moreover, the recent developments in parallel computing with ML offer new possibilities in terms of training and predicting speed and therefore makes their usage in real time systems feasible. The present study compares four ML algorithms for rainfall area detection and rainfall rate assignment during daytime, night-time and twilight using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path are applied as predictor variables. As machine learning algorithms, random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) are chosen. The comparison is realised in three steps. First, an extensive tuning study is carried out to customise each of the models. Secondly, the models are trained using the optimum values of model parameters found in the tuning study. Finally, the trained models are used to detect rainfall areas and to assign rainfall rates using an independent validation datasets which is compared against ground-based radar data. To train and validate the models, the radar-based RADOLAN RW product from the German Weather Service (DWD) is used which provides area-wide gauge-adjusted hourly precipitation information. Though the differences in the performance of the algorithms were rather small, NNET and AVNNET have been identified as the most suitable algorithms. On average, they showed the best performance in rainfall area delineation as well as in rainfall rate assignment. The fast computation time of NNET allows to work with large datasets as it is required in remote sensing based rainfall retrievals. However, since none of the algorithms performed considerably better that the others we conclude that research effort is needed in providing suitable predictors for rainfall rather than in optimizing by the choice of the ML algorithm.

  13. The Status of the Tropical Rainfall Measuring Mission (TRMM) after 2 Years in Orbit

    NASA Technical Reports Server (NTRS)

    Kummerow, C.; Simpson, J.; Thiele, O.; Barnes, W.; Chang, A. T. C.; Stocker, E.; Adler, R. F.; Hou, A.; Kakar, R.; Wentz, F.

    1999-01-01

    The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, in related modeling applications and in new datasets tailored specifically for these applications. This paper reports the latest results regarding the calibration of the TRMM Microwave Imager, (TMI), Precipitation Radar (PR) and Visible and Infrared Sensor (VIRS). For the TMI, a new product is in place that corrects for a still unknown source of radiation leaking in to the TMI receiver. The PR calibration has been adjusted upward slightly (by 0.6 dBZ) to better match ground reference targets, while the VIRS calibration remains largely unchanged. In addition to the instrument calibration, great strides have been made with the rainfall algorithms as well, with the new rainfall products agreeing with each other to within less than 20% over monthly zonally averaged statistics. The TRMM Science Data and Information System (TSDIS) has responded equally well by making a number of new products, including real-time and fine resolution gridded rainfall fields available to the modeling community. The TRMM Ground Validation (GV) program is also responding with improved radar calibration techniques and rainfall algorithms to provide more accurate GV products which will be further enhanced with the new multiparameter 10 cm radar being developed for TRMM validation and precipitation studies. Progress in these various areas has, in turn, led to exciting new developments in the modeling area where Data Assimilation, and Weather Forecast models are showing dramatic improvements after the assimilation of observed rainfall fields.

  14. The Severe Weather Outbreak of 10 November 2002: Lightning and Radar Analysis of Storms in the Deep South

    NASA Technical Reports Server (NTRS)

    Buechler, D. E.; McCaul, E. W., Jr.; Goodman, S. J.; Blakeslee, R. J.; Bailey, J. C.; Gatlin, P.

    2004-01-01

    On the afternoon and evening of 10 November 2002, the Midwest and Deep South were struck by a major outbreak of severe storms that produced some 80 tornadoes. In terms of number of tornadoes, this was the largest outbreak in the United States since November 1992. Some 32 of the tornadoes occurred in Tennessee, Mississippi, Alabama and Georgia, including several long-track killers. We use the North Alabama Lightning Mapping Array (LMA) and other data sources to perform a comprehensive analysis of the structure and evolution of the outbreak. Most of the Southern tornadoes occurred in isolated, fast-moving supercell storms that formed in warm, moist air ahead of a major cold front. Storms tended to form in lines parallel to storm cell motion, resulting in many communities being hit multiple times by severe storms that evening. Supercells in Tennessee produced numerous strong tornadoes with short to medium-length track paths, while the supercells further south produced several very long-track tornadoes. Radar data indicate that the Tennessee storms tended to split frequently, apparently limiting their ability to sustain long-lived tornadoes, while storms further south split at most one time. The differences between these storms appear to be related to the presence of stronger jetstream winds in Tennessee relative to those present in Mississippi, Alabama and Georgia. LMA-derived flash rates associated with most of the supercell storm cores were about 1-2 flashes per second. Rapid increases in lightning rates (or "jumps") occurred prior to tornado touchdown in many instances. Lightning "holes" (lightning-free regions associated with the echo-free vault) occurred in two of the Tennessee supercells. The complexity of the relationship between lightning and storm severity is revealed by the behavior of one Alabama supercell, which produced a peak flash rate of nearly 14 flashes per second, well after the end of its long-track tornado, while interacting and ultimately merging with a daughter supercell on its southwest flank. Close examination of this powerful storm indicates that its prodigious flash rate was the result of strong flash activity over an unusually large area, rather than a concentrated core of extremely high flash rate activity.

  15. Meteorological radar calibration

    NASA Technical Reports Server (NTRS)

    Hodge, D. B.

    1978-01-01

    A meteorological radar calibration technique is developed. It is found that the integrated, range corrected, received power saturates under intense rain conditions in a manner analogous to that encountered for the radiometric path temperature. Furthermore, it is found that this saturation condition establishes a bound which may be used to determine an absolution radar calibration for the case of radars operating at attenuating wavelengths. In the case of less intense rainfall or for radars at nonattenuating wavelengths, the relationship for direct calibration in terms of an independent measurement of radiometric path temperature is developed. This approach offers the advantage that the calibration is in terms of an independent measurement of the rainfall through the same elevated region as that viewed by the radar.

  16. Quantitative rainfall metrics for comparing volumetric rainfall retrievals to fine scale models

    NASA Astrophysics Data System (ADS)

    Collis, Scott; Tao, Wei-Kuo; Giangrande, Scott; Fridlind, Ann; Theisen, Adam; Jensen, Michael

    2013-04-01

    Precipitation processes play a significant role in the energy balance of convective systems for example, through latent heating and evaporative cooling. Heavy precipitation "cores" can also be a proxy for vigorous convection and vertical motions. However, comparisons between rainfall rate retrievals from volumetric remote sensors with forecast rain fields from high-resolution numerical weather prediction simulations are complicated by differences in the location and timing of storm morphological features. This presentation will outline a series of metrics for diagnosing the spatial variability and statistical properties of precipitation maps produced both from models and retrievals. We include existing metrics such as Contoured by Frequency Altitude Diagrams (Yuter and Houze 1995) and Statistical Coverage Products (May and Lane 2009) and propose new metrics based on morphology, cell and feature based statistics. Work presented focuses on observations from the ARM Southern Great Plains radar network consisting of three agile X-Band radar systems with a very dense coverage pattern and a C Band system providing site wide coverage. By combining multiple sensors resolutions of 250m2 can be achieved, allowing improved characterization of fine-scale features. Analyses compare data collected during the Midlattitude Continental Convective Clouds Experiment (MC3E) with simulations of observed systems using the NASA Unified Weather Research and Forecasting model. May, P. T., and T. P. Lane, 2009: A method for using weather radar data to test cloud resolving models. Meteorological Applications, 16, 425-425, doi:10.1002/met.150, 10.1002/met.150. Yuter, S. E., and R. A. Houze, 1995: Three-Dimensional Kinematic and Microphysical Evolution of Florida Cumulonimbus. Part II: Frequency Distributions of Vertical Velocity, Reflectivity, and Differential Reflectivity. Mon. Wea. Rev., 123, 1941-1963, doi:10.1175/1520-0493(1995)123<1941:TDKAME>2.0.CO;2.

  17. Observations of the marine environment from spaceborne side-looking real aperture radars

    NASA Technical Reports Server (NTRS)

    Kalmykov, A. I.; Velichko, S. A.; Tsymbal, V. N.; Kuleshov, Yu. A.; Weinman, J. A.; Jurkevich, I.

    1993-01-01

    Real aperture, side looking X-band radars have been operated from the Soviet Cosmos-1500, -1602, -1766 and Ocean satellites since 1984. Wind velocities were inferred from sea surface radar scattering for speeds ranging from approximately 2 m/s to those of hurricane proportions. The wind speeds were within 10-20 percent of the measured in situ values, and the direction of the wind velocity agreed with in situ direction measurements within 20-50 deg. Various atmospheric mesoscale eddies and tropical cyclones were thus located, and their strengths were inferred from sea surface reflectivity measurements. Rain cells were observed over both land and sea with these spaceborne radars. Algorithms to retrieve rainfall rates from spaceborne radar measurements were also developed. Spaceborne radars have been used to monitor various marine hazards. For example, information derived from those radars was used to plan rescue operations of distressed ships trapped in sea ice. Icebergs have also been monitored, and oil spills were mapped. Tsunamis produced by underwater earthquakes were also observed from space by the radars on the Cosmos 1500 series of satellites. The Cosmos-1500 satellite series have provided all weather radar imagery of the earths surface to a user community in real time by means of a 137.4 MHz Automatic Picture Transmission channel. This feature enabled the radar information to be used in direct support of Soviet polar maritime activities.

  18. Comparison Between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

    NASA Technical Reports Server (NTRS)

    Dworak, Richard; Bedka, Kristopher; Brunner, Jason; Feltz, Wayne

    2012-01-01

    Studies have found that convective storms with overshooting-top (OT) signatures in weather satellite imagery are often associated with hazardous weather, such as heavy rainfall, tornadoes, damaging winds, and large hail. An objective satellite-based OT detection product has been developed using 11-micrometer infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager. In this study, this method is applied to GOES-12 IRW data and the OT detections are compared with radar data, severe storm reports, and severe weather warnings over the eastern United States. The goals of this study are to 1) improve forecaster understanding of satellite OT signatures relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) evaluate the utility of an OT detection product for diagnosing hazardous convective storms. The coevolution of radar-derived products and satellite OT signatures indicates that an OT often corresponds with the highest radar echo top and reflectivity maximum aloft. Validation of OT detections relative to composite reflectivity indicates an algorithm false-alarm ratio of 16%, with OTs within the coldest IRW BT range (less than 200 K) being the most accurate. A significant IRW BT minimum typically present with an OT is more often associated with heavy precipitation than a region with a spatially uniform BT. Severe weather was often associated with OT detections during the warm season (April September) and over the southern United States. The severe weather to OT relationship increased by 15% when GOES operated in rapid-scan mode, showing the importance of high temporal resolution for observing and detecting rapidly evolving cloud-top features. Comparison of the earliest OT detection associated with a severe weather report showed that 75% of the cases occur before severe weather and that 42% of collocated severe weather reports had either an OT detected before a severe weather warning or no warning issued at all. The relationships between satellite OT signatures, severe weather, and heavy rainfall shown in this paper suggest that 1) when an OT is detected, the particular storm is likely producing heavy rainfall and/or possibly severe weather; 2) an objective OT detection product can be used to increase situational awareness and forecaster confidence that a given storm is severe; and 3) this product may be particularly useful in regions with insufficient radar coverage.

  19. Simulation of air- and spaceborne radar rain path attenuation estimation using the mirror image radar return

    NASA Astrophysics Data System (ADS)

    Liao, Liang; Meneghini, Robert; Iguchi, Toshio

    1998-08-01

    The mirror image rain echo, received through the double reflection of the radar from the surface, may provide useful information in estimating the rainfall rate form airborne and spaceborne weather radars. As the TRMM spaceborne weather radar has been successfully launched recently, issues regarding the utility of this measurement are pertinent and timely. In this study, having described a mirror image model, which yields the co- and cross-polarized components of the mirror image nd bistatic returns as a function of the radar parameters and the scattering properties of the rain and surface, several algorithms to estimate the path attenuation based on the mirror image returns are constructed. These methods generally use a difference between the direct and mirror image radar returns where the returns are taken at equally distant ranges above and 'below' the surface. In some implementations of the algorithm the return power from the surface is used as well. To test the accuracy of these algorithms, the first, mirror image and surface return powers are generated from measured raindrop size distributions,