Science.gov

Sample records for weather radar rainfall

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  3. 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.

  4. Estimates of cumulative rainfall over a large area by weather radar

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

    In this work we propose a technique for 15-minutes cumulative rainfall mapping, applied over Tuscany, using Italian weather radar networks together with the regional rain gauge network. In order to assess the accuracy of the radar-based rainfall estimates, we have compared them with spatial coincident rain gauge measurements. Precipitation at ground is our target observable: rain gauge measurements of such parameter have a so small error that we consider it negligible (especially if compared from what retrievable from radars). In order to make comparable the observations given from these two types of sensors, we have collected cumulative rainfall over areas a few tens of kilometres wide. The method used to spatialise rain gauges data has been the Ordinary Block Kriging. In this case the comparison results have shown a good correlation between the cumulative rainfall obtained from the rain gauges and those obtained by the radar measurements. Such results are encouraging in the perspective of using the radar observations for near real time cumulative rainfall nowcasting purposes. In addition the joint use of satellite instruments as SEVIRI sensors on board of MSG-3 satellite can add relevant information on the nature, spatial distribution and temporal evolution of cloudiness over the area under study. For this issue we will analyse several MSG-3 channel images, which are related to cloud physical characteristics or ground features in case of clear sky.

  5. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  7. Estimating the frequency of extreme rainfall using weather radar and stochastic storm transposition

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Spatial and temporal variability in extreme rainfall, and its interactions with land cover and the drainage network, is an important driver 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 commonly-made assumptions are rarely considered, and their impacts on flood risk estimates are poorly understood. This study presents an alternate framework for rainfall frequency analysis that couples stochastic storm transposition (SST) with "storm catalogs" developed from a ten-year high-resolution (15-min, 1-km2) radar rainfall dataset for the region surrounding Charlotte, North Carolina, USA. The SST procedure involves spatial and temporal resampling from these storm catalogs to reconstruct the regional climatology of extreme rainfall. SST-based intensity-duration-frequency (IDF) estimates are driven by the spatial and temporal rainfall variability from weather radar observations, are tailored specifically to the chosen watershed, and do not require simplifying assumptions of storm structure. We are able to use the SST procedure to reproduce IDF estimates from conventional methods for four urban watersheds in Charlotte. We demonstrate that extreme rainfall can vary substantially in time and in space, with potentially important flood risk implications that cannot be assessed using conventional techniques. SST coupled with high-resolution radar rainfall fields represents a useful alternative to conventional design storms for flood risk assessment, the full advantages of which can be realized when the concept is extended to flood frequency analysis using a distributed hydrologic model.

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

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  9. Weather radar measurements in data-driven rainfall-runoff models

    NASA Astrophysics Data System (ADS)

    Teschl, R.; Randeu, W. L.; Teschl, F.

    2009-04-01

    Meanwhile data-driven models have become established tools in the field of hydrology. Most of these models use rain gauge data as precipitation inputs. Weather radar data are rarely utilized in rainfall-runoff models basically because often these data are not available for disposal. But particularly the gapless spatial coverage of the weather radar is beneficial to detect also small rainfall cells over a catchment. But weather radar data entail disadvantages in data-driven models as well. By using gridded radar data instead of rain gauge measurements the number of input parameters generally increases and this may complicate the training process. If the radar grid element is small with respect to the catchment size the pixels usually have to be grouped in a certain way in order to avoid dozens of input parameters. This paper investigates how data-driven approaches like Artificial Neural Networks (ANN) and Model Trees (MT) handle larger numbers of precipitation inputs. The study area is the Sulm catchment in the south-west of Styria, Austria. This is a mountainous area which is often affected by rain showers in summer. ANNs and MTs were used to predict the runoff of a small catchment with 90 minutes lead-time (considering the 15 minutes temporal resolution of the dataset this is 6 time lags). Besides weather radar and rain gauge data the actual runoff is also taken as an input. The first approaches showed that the impact of the precipitation measurements (gauge and radar) in the data-driven approaches is low. The actual runoff is the determining factor in the prediction which becomes clear through the linear equations in the MTs. Whenever the coefficient for the actual runoff > 1 this is compensated by a negative bias. On the other hand smaller coefficients for the actual runoff result in higher biases whereas the coefficients for the precipitation inputs are low. Thus, precipitation inputs have little influence on the model output. The consideration of a modified training approach was to accentuate the significance of the precipitation data in the model. And the idea to achieve this was to let the model predict the difference between the runoff 90 minutes ahead (the former target) and the actual runoff. This new target vector - the runoff difference - has to be added to the actual runoff in order to gain the future runoff. Thus, once trained, the network output has to be added to the known actual runoff to obtain a prediction of the runoff 90 minutes ahead. The idea to let the models predict the runoff difference attributed more weight to the precipitation data and minimized the influence of the actual runoff on the model output. This has a positive influence on the timing error of the prediction (although a timing error is still visible) and improved the performance of both models. The efficiency coefficient of the MT lies at 86 % compared to 84% in the first approach. The ANN performed consistently better than the MT and exhibits now an efficiency coefficient of over 92 % compared to 90 % before. Also other performance measures as mean squared and mean absolute error could be decreased.

  10. 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.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    Rainfall intensity estimation from radar is known to be prone to different sources of uncertainty, both in the detection and in the processing phase. These sources of uncertainty are especially relevant when severe rainfall rates are considered, thus calling for the adoption of advanced methods for the estimation of the rainfall rate from radar observations. We introduce a quasi-real time procedure for the adaptive estimation of the coefficients of the Z-R relation that links radar reflectivity to rainfall rate. The proposed quasi-real time calibration can grant Z-R relationships consistent with the evolution of the event while the use of a spatially adaptive approach makes the technique amenable to be applied in large areas with complex orography. The aim is to define a simple and operative methodology suitable for a systematic and possibly unsupervised application, capable to reconstruct the whole spectrum of intensities occurred during an intense rainfall event. We propose to readjust the power-law equation commonly used to transform reflectivity to rainfall intensity at each time step, calibrating its parameters by means of Z-R pairs collected in the time proximity of the considered instant. Z-R data are filtered with a reflectivity threshold, which varies in time, in order to discriminate between the presence and absence of rainfall. For every location, the spatial calibration domain is limited to the rain gauges belonging to a neighbourhood. Z-R coefficients are estimated for each location and each time step by minimizing the standard deviation between observed and estimated rainfall, through a non-linear procedure. The case study includes a set of 16 severe rainfall events occurred in the north-west of Italy. The technique outperforms the classical estimation methods for most of the analysed events and shows significant potential for operational uses. The determination coefficient undergoes up to 30% improvements and the BIAS values are reduced, for stratiform events, up to 80% of the values obtained with the classical non-adaptive Z-R relations.

  13. 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

  14. Comparison of radar data versus rainfall data.

    PubMed

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

    2015-01-01

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

  15. 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.

  16. 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.

  17. 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

  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. 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 ...

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is performed. Then hydrologic component of the runoff hydrographs, peak flows and total runoffs from the estimated rainfall and the observed rainfall are compared. The results show that hydrologic components have high fluctuations depending on storm rainfall event. Thus, it is necessary to choose appropriate radar rainfall data derived from the above radar rainfall transform formulas to analyze the runoff of radar rainfall. The simulated hydrograph by radar in the three basins of agricultural areas is more similar to the observed hydrograph than the other three basins of mountainous areas. Especially the peak flow and shape of hydrograph of the agricultural areas is much closer to the observed ones than that of mountainous areas. This result comes from the difference of radar rainfall depending on the basin elevation. Therefore we need the examination of radar rainfall transform formulas following rainfall event and runoff analysis based on basin elevation for the improvement of radar rainfall application. Acknowledgment This study was financially supported by the Construction Technology Innovation Program(08-Tech-Inovation-F01) through the Research Center of Flood Defence Technology for Next Generation in Korea Institute of Construction & Transportation Technology Evaluation and Planning(KICTEP) of Ministry of Land, Transport and Maritime Affairs(MLTM)

  2. 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.

  3. 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.

  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:

  5. 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…

  6. 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…

  7. 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.

  8. 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.

  9. 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.

  10. 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...

  11. 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.

  12. 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.

  13. Analyses of the warm season rainfall climatology of the northeastern US using regional climate model simulations and radar rainfall fields

    NASA Astrophysics Data System (ADS)

    Yeung, June K.; Smith, James A.; Villarini, Gabriele; Ntelekos, Alexandros A.; Baeck, Mary Lynn; Krajewski, Witold F.

    2011-02-01

    We examine the warm season (April-September) rainfall climatology of the northeastern US through analyses of high-resolution radar rainfall fields from the Hydro-NEXRAD system and regional climate model simulations using the weather research and forecasting (WRF) model. Analyses center on the 5-year period from 2003 to 2007 and the study area includes the New York-New Jersey metropolitan region covered by radar rainfall fields from the Fort Dix, NJ WSR-88D. The objective of this study is to develop and test tools for examining rainfall climatology, with a special focus on heavy rainfall. An additional emphasis is on rainfall climatology in regions of complex terrain, like the northeastern US, which is characterized by land-water boundaries, large heterogeneity in land use and cover, and mountainous terrain in the western portion of the region. We develop a 5-year record of warm season radar rainfall fields for the study region using the Hydro-NEXRAD system. We perform regional downscaling simulations for the 5-year study period using the WRF model. Radar rainfall fields are used to characterize the interannual, seasonal and diurnal variation of rainfall over the study region and to examine spatial heterogeneity of rainfall. Regional climate model simulations are characterized by a wet bias in the rainfall fields, with the largest bias in the high-elevation regions of the model domain. We show that model simulations capture broad features of the interannual, seasonal, and diurnal variation of rainfall. Model simulations do not capture spatial gradients in radar rainfall fields around the New York metropolitan region and land-water boundaries to the east. The model climatology of convective available potential energy (CAPE) is used to interpret the regional distribution of warm season rainfall and the seasonal and diurnal variability of rainfall. We use hydrologic and meteorological observations from July 2007 to examine the interactions of land surface processes and rainfall from a regional perspective.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-05-01

    The efficacy of dual polarimetric radar for quantitative precipitation estimation (QPE) is firmly established. Specifically, rainfall retrievals using combinations of reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase (KDP) have advantages over traditional Z-R methods because more information about the drop size distribution and hydrometeor type are available. In addition, dual-polarization radar measurements are generally less susceptible to error and biases due to the presence of ice in the sampling volume. A number of methods have been developed to estimate rainfall from dual-polarization radar measurements. However, the robustness of these techniques in different precipitation regimes is unknown. Because the National Weather Service (NWS) will soon upgrade the WSR 88-D radar network to dual-polarization capability, it is important to test retrieval algorithms in different meteorological environments in order to better understand the limitations of the different methodologies. An important issue in dual-polarimetric rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? At Colorado State University (CSU), a "blended" algorithm has been developed and used for a number of years to estimate rainfall based on ZH, ZDR, and KDP (Cifelli et al. 2002). The rainfall estimators for each sampling volume are chosen on the basis of fixed thresholds, which maximize the measurement capability of each polarimetric variable and combinations of variables. Tests have shown, however, that the retrieval is sensitive to the calculation of ice fraction in the radar volume via the difference reflectivity (ZDP - Golestani et al. 1989) methodology such that an inappropriate estimator can be selected in situations where radar echo is relatively weak (< 40 dBZ). In this study, a new blended rainfall algorithm is developed using hydrometeor identification (HID) to drive the rainfall estimation algorithm. HID discrimination for rainfall application namely, (1) all rain, (2) mixed precipitation, and (3) all ice, is used to guide the selection of the most appropriate rainfall estimator. Data collected from the CSU-CHILL radar and a network of rain gauges are used to test the performance of the new algorithm in a variety of precipitation situations. The results are compared to similar results using the algorithm from the National Severe Storm Laboratory (NSSL), derived from Oklahoma precipitation events ( Ryzhkov et al. 2005 ). The applicability of the method derived from Oklahoma observations to Colorado precipitation events is also explored.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields

    NASA Astrophysics Data System (ADS)

    Thorndahl, Søren; Smith, James A.; Baeck, Mary Lynn; Krajewski, Witold F.

    2014-07-01

    In this paper, we develop a storm catalog of heavy rainfall events for a region centered on the Milwaukee, Wisconsin WSR-88D (Weather Surveillance Radar - 1988 Doppler) radar. The study region includes portions of southern Wisconsin, northern Illinois and Lake Michigan. The long-term objective of this study is to develop rainfall frequency analysis methods based on a storm catalog of major rain events. The specific objectives of this study are to develop a long-term catalog of high-resolution radar rainfall fields and characterize key features of the space-time variability of rainfall. The research questions that underlie these objectives are: 1) What are the spatial heterogeneities of rainfall over the study region for major flood-producing storm systems? 2) What are the key elements of storm evolution that control the scale-dependent properties of extreme rainfall? The storm catalog contains a record of the 50 “largest” storm days during the 1996-2011 observation period. We show that mean rainfall for the 50 largest storm days exhibits pronounced spatial heterogeneity with a broad maximum in western Wisconsin and a minimum in the eastern portion of the study region over Lake Michigan. We also show that there is a narrow line of maximum mean rainfall extending from west to east along the Wisconsin-Illinois border. This feature is tied to a maximum in the probability of daily rainfall exceeding 100 mm. There are characteristic elements to the storm life cycle of heavy rainfall days that relate to size, structure and evolution of heavy rainfall. Extreme rainfall is also linked with severe weather (tornados, large hail and damaging wind). The diurnal cycle of rainfall for heavy rain days is characterized by an early peak in the largest rainfall rates, an afternoon-evening peak in rain area exceeding 25 mm h- 1 and development of a large stratiform rain area during the night and early morning.

  2. 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.

  3. 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.

  4. 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.

  5. Representing rainfall uncertainties using radar ensembles: generation of radar based rainfall ensembles for QPE and QPF

    NASA Astrophysics Data System (ADS)

    Sempere-Torres, D.; Llort, X.; Roca, J.; Pegram, G.

    2009-04-01

    In the last years, new comprehension of the physics underlying the radar measurements as well as new technological advancements have allowed radar community to propose better algorithms and methodologies and significant advancements have been achieved in improving Quantitative Precipitation Estimates (QPE) and Quantitative Precipitation forecasting (QPF) by radar. Thus the study of the 2D uncertainties field associated to these estimates has become an important subject, specially to enhance the use of radar QPE and QPF in hydrological studies, as well as in providing a reference for satellite precipitations measurements. In this context the use of radar-based rainfall ensembles (i.e. equiprobable rainfall field scenarios generated to be compatible with the observations/forecasts and with the inferred structure of the uncertainties) has been seen as an extremely interesting tool to represent their associated uncertainties. The generation of such radar ensembles requires first the full characterization of the 3D field of associated uncertainties (2D spatial plus temporal), since rainfall estimates show an error structure highly correlated in space and time. A full methodology to deal with this kind of radar-based rainfall ensembles is presented. Given a rainfall event, the 2D uncertainty fields associated to the radar estimates are defined for every time step using a benchmark, or reference field, based on the best available estimate of the rainfall field. This benchmark is built using an advanced non parametric interpolation of a dense raingauge network able to use the spatial structure provided by the radar observations, and is confined to the region in which this combination could be taken as a reference measurement (Velasco-Forero et al. 2008, doi:10.1016/j.advwatres.2008.10.004). Then the spatial and temporal structures of these uncertainty fields are characterized and a methodology to generate consistent multiple realisations of them is used to generate the radar-based rainfall ensembles scenarios. This methodology, based on the improvement of the "String of Beads" model (Pegram and Clothier, 2001, doi:10.1016/S0022-1694(00)00373-5), is designed to preserve their main characteristics, such as anisotropy and the temporal variations of their spatial correlation. The discussion of the results on a illustrative case study and their potential interest in hydrological applications will be also discussed .

  6. 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.

  7. High-resolution rainfall estimation for Helsinki urban area using Helsinki radar network

    NASA Astrophysics Data System (ADS)

    Rojas, Laura; Nordling, Kalle; Cremonini, Roberto; Moisseev, Dmitri; Chandrasekar, Venkatachalam

    2014-05-01

    High resolution precipitation data is a crucial factor for hydrological applications in urban areas. Small fluctuations in precipitation fields are of great importance considering the fast response of urban catchments due to the dominance of impervious surfaces. High resolution precipitation observations are needed in order to characterize these fluctuations. Weather radar provides high spatial resolution precipitation estimations. However, the quality of its observations in an urban environment is significantly degraded, among other things, by ground clutter and beam-blockage. A solution for this problem is to use a radar network, where the data gaps of one radar will be filled by using observations from the others. Very few cities have dedicated weather radar networks. In some cities, like Helsinki, there are several weather radars covering the metropolitan area, but they are operated by different organizations. In this study, we show how such systems can be used to build a network and what is the advantage of using radarnetworks for estimating precipitation in urban catchments. The urban Helsinki area is covered by observations from three individual-purpose C-band weather radars (Helsinki University's Kumpula (KUM), Vaisala Oy's Kerava (KER) and Finnish Meteorological Institute's Vantaa (VAN)). We used the data from these radars to form a network and we design a similar task which runs at the same time in each radar couple of times per day. Nonetheless, it is challenging to make them observe at the same area at exactly the same time, which could lead to fast changing, short precipitation events being missed. Hence, synchronization and temporal resolution are the main concerns when building a network. Consequently, to decrease the impact of these restrictions in the Helsinki radar network we propose the use of the optic flow interpolation algorithm to retrieve information in between two radar observations and use the retrieved dataset from the three radars to estimate rainfall. The accuracy of this method is studied by comparing the composite rainfall estimation with both single radar observations and ground measurements.

  8. 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.

  9. 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.

  10. 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....

  11. 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....

  12. 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....

  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, 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....

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

    PubMed

    Ritchie, S A

    1993-06-01

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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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... radar equipment is installed in the aircraft. (b) No person may begin a flight under IFR or night...

  3. 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... radar equipment is installed in the aircraft. (b) No person may begin a flight under IFR or night...

  4. 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... radar equipment is installed in the aircraft. (b) No person may begin a flight under IFR or night...

  5. 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... radar equipment is installed in the aircraft. (b) No person may begin a flight under IFR or night...

  6. 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... radar equipment is installed in the aircraft. (b) No person may begin a flight under IFR or night...

  7. 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.

  8. 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.

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. A new radar technique for satellite rainfall algorithm development

    NASA Technical Reports Server (NTRS)

    Jameson, Arthur R.

    1987-01-01

    A potential new radar parameter was investigated for measuring rainfall, namely the summation of the phase shifts at horizontal and vertical polarizations due to propagation through precipitation. The proposed radar technique has several potential advantages over other approaches because it is insensitive to the drop size distribution and to the shapes of the raindrops. Such a parameter could greatly assist the development of satellite rainfall estimation algorithms by providing comparative measurements near the ground. It could also provide hydrologically useful information for such practical applications as urban hydrology. Results of the investigation showed that the parameters can not be measured by radar. However, a closely related radar parameter, propagation differential phase shift, can be readily measured using a polarization diversity radar. It is recommended that propagation differential phase shift be further investigated and developed for radar monitoring of rainfall using a polarization agile radar. It is also recommended that a prototype multiple frequency microwave link be constructed for attenuation measurements not possible by existing radar systems.

  15. 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. ...

  16. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  18. 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

  19. 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.

  20. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  2. SUB-PIXEL SCALE RAINFALL VARIABILITY AND THE EFFECTS ON SEPARATION OF RADAR AND GAUGE RAINFALL ERRORS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    As long recognized, one of the primary sources of the discrepancies in the 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 radar rainfall estimates and gauge measurements are...

  3. 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.

  4. Simulation of radar reflectivity and surface measurements of rainfall

    NASA Technical Reports Server (NTRS)

    Chandrasekar, V.; Bringi, V. N.

    1987-01-01

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

  5. 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.

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

    PubMed

    Quirmbach, M; Schultz, G A

    2002-01-01

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

  7. Rainfall Intensity and Drop Size Measurements with Polarimetric X-band Radar

    NASA Astrophysics Data System (ADS)

    Martner, B. E.; Matrosov, S. Y.; Clark, K. A.; Tokay, A.

    2002-12-01

    Most studies for developing quantitative, scanning radar estimates of rainfall have been conducted using 3-GHz (S-band, 10-cm wavelength) weather surveillance radar systems, in order to avoid attenuation effects that significantly impair reflectivity (Z) measurements at shorter wavelengths. However, the recent extension of polarimetric differential phase methods to shorter-wave systems, including X-band (9 GHz, 3-cm), now allows these generally smaller radars to also be used for quantitative rain estimations. Differential phase offers rainfall estimates that are independent of reflectivity data, as well as a way to adjust for partial attenuation effects in X-band reflectivity data. Rainfall intensity and accumulation measurements based on specific differential phase (KDP) alone offer many advantages over traditional reflectivity-based rain estimates. In this study, rain observations obtained with a polarimetric X-band scanning radar are processed with algorithms that estimate rain rate using differential phase, reflectivity, and a combination of the radar's measurements of differential phase with attenuation-corrected reflectivity and differential reflectivity (ZDR). The attenuation-corrected ZDR measurements are also used to estimate mean raindrop diameter. Demonstration measurements were obtained at Wallops Island, Virginia, in 15 storms with rain rates ranging from very light to heavy. The radar estimates are compared with measurements by tipping bucket rain gauges and raindrop disdrometers located a few kilometers away. It was found that the combined Z-ZDR-KDP estimator provided the closest agreement with gauge measurements, having an overall 22 per cent relative standard deviation of differences. The attenuation-adjusted ZDR estimates of mean drop diameter also compared well with the disdrometer measurements.

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

    NASA Astrophysics Data System (ADS)

    Wei, Chih-Chiang

    2014-06-01

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

  10. 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).

  11. 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).

  12. 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.

  13. 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.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

  16. 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.

  17. Transforming Nexrad Radar Rainfall Maps to Flood Inundation Maps

    NASA Astrophysics Data System (ADS)

    Maidment, D. R.; Robayo, O.

    2004-12-01

    The Arc Hydro geographic data model for representing water resources features of the landscape is a customization of ArcGIS for representation of water resources features of the landscape. Arc Hydro is used here to integrate the HEC-HMS and HEC-RAS flood simulation models so as to transform Nexrad radar rainfall data into flood inundation maps through the HEC models. An automated workflow sequence is established using Map2Map: an ArcGIS version 9 toolbox and Model Builder that accomplishes all the desired data transformations between the GIS and the two hydrologic models including time series data exchange for rainfall, flows and water surface elevations. An example application is presented for Salado and Rosillo Creeks in San Antonio.

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

    NASA Astrophysics Data System (ADS)

    Chen, Haonan

    Currently, the Next Generation (NEXRAD) radar network, a joint effort of the U.S. Department of Commerce (DOC), Defense (DOD), and Transportation (DOT), provides radar data with updates every five-six minutes across the United States. This network consists of about 160 S-band (2.7 to 3.0 GHz) radar sites. At the maximum NEXRAD range of 230 km, the 0.5 degree radar beam is about 5.4 km above ground level (AGL) because of the effect of earth curvature. Consequently, much of the lower atmosphere (1-3 km AGL) cannot be observed by the NEXRAD. To overcome the fundamental coverage limitations of today's weather surveillance radars, and improve the spatial and temporal resolution issues, the National Science Foundation Engineering Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) was founded to revolutionize weather sensing in the lower atmosphere by deploying a dense network of shorter-range, low-power X-band dual-polarization radars. The distributed CASA radars are operating collaboratively to adapt the changing atmospheric conditions. Accomplishments and breakthroughs after five years operation have demonstrated the success of CASA program. Accurate radar quantitative precipitation estimation (QPE) has been pursued since the beginning of weather radar. For certain disaster prevention applications such as flash flood and landslide forecasting, the rain rate must however be measured at a high spatial and temporal resolution. To this end, high-resolution radar QPE is one of the major research activities conducted by the CASA community. A radar specific differential propagation phase (Kdp)-based QPE methodology has been developed in CASA. Unlike the rainfall estimation based on the power terms such as radar reflectivity (Z) and differential reflectivity (Zdr), Kdp-based QPE is less sensitive to the path attenuation, drop size distribution (DSD), and radar calibration errors. The CASA Kdp-based QPE system is also immune to the partial beam blockage and hail contamination. The performance of the CASA QPE system is validated and evaluated by using rain gauges. In CASA's Integrated Project 1 (IP1) test bed in Southwestern Oklahoma, a network of 20 rainfall gauges is used for cross-comparison. 40 rainfall cases, including severe, multicellular thunderstorms, squall lines and widespread stratiform rain, that happened during years 2007 - 2011, are used for validation and evaluation purpose. The performance scores illustrate that the CASA QPE system is a great improvement compared to the current state-of-the-art. In addition, the high-resolution CASA QPE products such as instantaneous rainfall rate map and hourly rainfall amount measurements can serve as a reliable input for various distributed hydrological models. The CASA QPE system can save lived and properties from hazardous flash floods by incorporating hydraulic and hydrologic models for flood monitoring and warning.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Weather Radars and Lidar for Observing the Atmosphere

    NASA Astrophysics Data System (ADS)

    (Vivek) Vivekanandan, J.

    2010-05-01

    The Earth Observing Laboratory (EOL) at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado develops and deploys state-of-the-art ground-based radar, airborne radar and lidar instruments to advance scientific understanding of the earth system. The ground-based radar (S-Pol) is equipped with dual-wavelength capability (S-band and Ka-band). S-Pol is the only transportable radar in the world. In order to capture faster moving weather events such as tornadoes and record observations of clouds over rugged mountainous terrain and ocean, an airborne radar (ELDORA) is used. It is the only airborne Doppler meteorological radar that is able to detect motions in the clear air. The EOL is in the process of building the first phase of a three phase dual wavelength W/Ka-band airborne cloud radar to be called the HIAPER Cloud Radar (HCR). This phase is a pod based W-band radar system with scanning capability. The second phase will add pulse compression and polarimetric capability to the W-band system, while the third phase will add complementary Ka-band radar. The pod-based radar is primarily designed to fly on the Gulfstream V (GV) and C-130 aircraft. The envisioned capability of a millimeter wave radar system on GV is enhanced by coordination with microwave radiometer, in situ probes, and especially by the NCAR GV High-Spectral Resolution Lidar (HSRL) which is also under construction. The presentation will describe the capabilities of current instruments and also planned instrumentation development.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Adjusting weather radar data to rain gauge measurements with data-driven models

    NASA Astrophysics Data System (ADS)

    Teschl, Reinhard; Randeu, Walter; Teschl, Franz

    2010-05-01

    Weather radar networks provide data with good spatial coverage and temporal resolution. Hence they are able to describe the variability of precipitation. Typical radar stations determine the rain rate for every square kilometre and make a full volume scan within about 5 minutes. A weakness however, is their often poor metering precision limiting the applicability of the radar for hydrological purposes. In contrast to rain gauges, which measure precipitation directly on the ground, the radar determines the reflectivity aloft and remote. Due to this principle, several sources of possible errors occur. Therefore improving the radar estimates of rainfall is still a vital topic in radar meteorology and hydrology. This paper presents data-driven approaches to improve radar estimates of rainfall by mapping radar reflectivity measurements Z to rain gauge data R. The analysis encompasses several input configurations and data-driven models. Reflectivity measurements at a constant altitude and the vertical profiles of reflectivity above a rain gauge are used as input parameters. The applied models are Artificial Neural Network (ANN), Model Tree (MT), and IBk a k-nearest-neighbour classifier. The relationship found between the data of a rain gauge and the reflectivity measurements is subsequently applied to another site with comparable terrain. Based on this independent dataset the performance of the data-driven models in the various input configurations is evaluated. For this study, rain gauge and radar data from the province of Styria, Austria, were available. The data sets extend over a two-year period (2001 and 2002). The available rain gauges use the tipping bucket principle with a resolution of 0.1 mm. Reflectivity measurements are obtained from the Doppler weather radar station on Mt. Zirbitzkogel (by courtesy of AustroControl GmbH). The designated radar is a high-resolution C-band weather-radar situated at an altitude of 2372 m above mean sea level. The data-driven models exhibit different performances on the various input configurations. Also data transformations were applied. The logarithm recommends itself for this transformation because the original Z-R-relationship is a power function, and the logarithm linearises this non-linear relationship. The MT which is a piecewise linear model performs best on logarithmised data. The IBk works well when transforming the reflectivity data in rain rate first. Overall the ANN exhibits the best performance showing a 10 % improvement in correlation and RMSE compared to the standard Z-R-relationship. When applying the vertical profile of reflectivity as input parameter, the correlation exhibits a more than 30 % improvement. The results indicate that the vertical profile of reflectivity provided by weather radars yields not only information on the type of precipitation, whether it is stratiform or convective. In data-driven models the vertical profile of reflectivity can help to get better estimates of rain rates on the ground, even in mountainous terrain without low-altitude radar measurements.

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

    PubMed

    Krämer, S; Verworn, H R

    2009-01-01

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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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

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

    SciTech Connect

    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.

  20. Hydroclimatologic Analyses of Extreme Rainfall and Flooding in Atlanta, Georgia Using Long-Term Radar-Rainfall Datasets

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    A 10-year radar rainfall dataset is being developed for the Atlanta, Georgia metropolitan area using the Hydro-NEXRAD algorithms. Radar rainfall fields are constructed at 15 minute time resolution and 1 km spatial resolution; observations from a dense network of rain gages are used for multiplicative bias correction. The high-resolution dataset will permit the investigation of urban effects on the initiation and evolution of heavy rainfall events. In addition, the climatology of extreme rainfall-runoff relationships will be examined with the aim of improving the understanding of the water balance and flood response of urban catchments during extreme rainfall events. Analyses relating the temporal and spatial distribution of rainfall to basin scale and land-use/land-cover characteristics will assist in developing urban flood frequency relationships. Events of particular interest are the floods of September 20-21, 2009 and May 3-4, 2010, which caused heavy damage and fatalities in portions of the southeastern US including Atlanta. Similar bias-corrected radar datasets in development for the Baltimore, Charlotte, and Milwaukee metropolitan areas will allow for the comparison of climatology of extreme rainfall and urban flooding in different regions of the United States and under different climate regimes.

  1. 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.

  2. A dual frequency 10 cm Doppler weather radar

    NASA Astrophysics Data System (ADS)

    Glover, K. M.; Armstrong, G. M.; Bishop, A. W.; Banis, K. J.

    A summary is given of the design concepts underlying a new 10-cm band dual frequency Doppler weather radar under development at the Air Force Geophysics Laboratory. Primary emphasis in the design is placed on the system performance in a clutter environment, and the technique used to extend the radar's unambiguous range and velocity span is an important, but secondary, consideration. The design includes the use of fault tolerance and/or fault location methods at critical locations in the system and automated calibration techniques for quasi-continuous monitoring of system performance. The approach followed for minimizing range and velocity ambiguities used in this radar is a uniform pulse train version of the Doviak et al. (1978) dual sampling (batch) technique.

  3. Impact of radar data assimilation for the simulation of a heavy rainfall case in central Italy using WRF-3DVAR

    NASA Astrophysics Data System (ADS)

    Maiello, I.; Ferretti, R.; Gentile, S.; Montopoli, M.; Picciotti, E.; Marzano, F. S.; Faccani, C.

    2014-09-01

    The aim of this study is to investigate the role of the assimilation of Doppler weather radar (DWR) data in a mesoscale model for the forecast of a heavy rainfall event that occurred in Italy in the urban area of Rome from 19 to 22 May 2008. For this purpose, radar reflectivity and radial velocity acquired from Monte Midia Doppler radar are assimilated into the Weather Research Forecasting (WRF) model, version 3.4.1. The general goal is to improve the quantitative precipitation forecasts (QPF): with this aim, several experiments are performed using the three-dimensional variational (3DVAR) technique. Moreover, sensitivity tests to outer loops are performed to include non-linearity in the observation operators. In order to identify the best initial conditions (ICs), statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a large impact on both the position of convective cells and on the rainfall forecast of the analyzed event. A positive impact is also found if they are ingested together with conventional observations. Sensitivity to the use of two or three outer loops is also found if DWR data are assimilated together with conventional data.

  4. Artificial neural network estimation of rainfall intensity from radar observations

    NASA Astrophysics Data System (ADS)

    Orlandini, Stefano; Morlini, Isabella

    2000-10-01

    Volumetric scans of radar reflectivity Z and gage measurements of rainfall intensity R are used to explore the capabilities of three artificial neural networks to identify and reproduce the functional relationship between Z and R. The three networks are a multilayer perceptron, a Bayesian network, and a radial basis function network. For each of them, numerical experiments are conducted incorporating in the network inputs different descriptions of the space-time variability of Z. Space variability refers to the observations of Z along the vertical atmospheric profile, at 11 constant altitude plan position indicator levels, namely ZT = (Z1,…,Z11). Time variability refers to the observations of Z at the time intervals prior to that for which the estimate of R is provided. Space variability is evaluated by performing a principal component analysis over standardized values of Z, namely Z˜, and the first two principal components of Z˜ (which describe 91% of the original variance) are used to synthesize the elements of Z into fewer orthogonal inputs for the networks. Network predictions significantly improve when the models are trained with the two principal components of Z˜ with respect to the case in which only Z1 is used. Increasing the time horizon further improves the performances of the Bayesian network but is found to worsen the performances of the other two networks.

  5. 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

  6. 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.

  7. 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.

  8. Processing of Indian Doppler Weather Radar data for mesoscale applications

    NASA Astrophysics Data System (ADS)

    Roy Bhowmik, S. K.; Sen Roy, Soma; Srivastava, Kuldeep; Mukhopadhay, B.; Thampi, S. B.; Reddy, Y. K.; Singh, Hari; Venkateswarlu, S.; Adhikary, Sourav

    2011-03-01

    This paper demonstrates the usefulness of Indian Doppler Weather Radar (DWR) data for nowcasting applications, and assimilation into a mesoscale Numerical Weather Prediction (NWP) model. Warning Decision Support System Integrated Information (WDSS-II) developed by National Severe Storm Laboratory (NSSL) and Advanced Regional Prediction System (ARPS) developed at the Centre for Analysis and Prediction, University of Oklahoma are used for this purpose. The study reveals that the WDSS-II software is capable of detecting and removing anomalous propagation echoes from the Indian DWR data. The software can be used to track storm cells and mesocyclones through successive scans. Radar reflectivity mosaics are created for a land-falling tropical cyclone—Khaimuk of 14 November 2008 over the Bay of Bengal using observations from three DWR stations, namely, Visakhapatnam, Machilipatnam and Chennai. Assimilation of the quality-controlled radar data (DWR, Chennai) of the WDSS-II software in a very high-resolution NWP model (ARPS) has a positive impact for improving mesoscale prediction. This has been demonstrated for a land-falling tropical cyclone Nisha of 27 November 2008 of Tamil Nadu coast. This paper also discusses the optimum scan strategy and networking considerations. This work illustrates an important step of transforming research to operation.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. Use of radar rainfall estimates in hydrological models: an assessment of predictive uncertainty

    NASA Astrophysics Data System (ADS)

    Borga, M.

    2003-04-01

    Radar estimates of rainfall are being increasingly applied to flood forecasting applications. Errors are inherent both in the process of estimating rainfall from radar and in the modelling of the rainfall-runoff transformation. This paper addresses the problem of evaluating the impact of the rainfall-runoff model parameter uncertainty on the propagation of radar errors trough the hydrological model. Model parameter uncertainty is explicitly accounted for by use of the GLUE (Generalized Likelihood Uncertainty Estimation; Beven and Binley, 1992). The GLUE procedure is used in this study as a means of hydrological model comparison using different rainfall input, provided by dense rain gage networks and by radar estimates according to various processing scenarios. The uncertainty assessment is carried out here through application of radar-estimated precipitation to a lumped rainfall-runoff model for the Brue catchment, a medium-sized watershed located in Somerset, south-west England. The analysis framework allows to evaluate both the wideness of the uncertainty limits and the percentage of observations included in the limits, with varying the behavioural threshold. This helps to assess the impact of radar rainfall errors on the output of a hydrological model previously conditioned using rainfall data from a dense raingauge network. The evaluation is reported in terms of both structural validity and predictive capability of the resulting model output. Several features are worth summarising here. Runoff simulations appear very sensitive to the impact of errors related to variability of reflectivity with height, which dominate the radar error structure. The runoff model defined by using unadjusted radar estimates for higher beam elevations is structurally invalid due to poorly defined input data. Results show the critical importance of proper adjustment of radar estimates. Uncertainty affecting runoff predictions from adjusted radar data are close to those generated by using a very dense raingage network, at least for the lowest radar scan. Use of the type of analysis proposed here provides a clear view of the relative effects of input and parameter uncertainty upon model output and indeed is a valuable tool in analysing and ranking the sources of predictive uncertainty. It is envisaged that, being explicit about the levels of uncertainty, limitations within the radar processing algorithm and the hydrological model can be improved upon, or additional data can be acquired in order to reduce the predictive uncertainty.

  15. 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.

  16. A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis

    NASA Astrophysics Data System (ADS)

    Bech, Joan; Pineda, Nicolau; Rigo, Tomeu; Aran, Montserrat; Amaro, Jéssica; Gayà, Miquel; Arús, Joan; Montanyà, Joan; der Velde, Oscar van

    2011-06-01

    This study presents an analysis of a severe weather case that took place during the early morning of the 2nd of November 2008, when intense convective activity associated with a rapidly evolving low pressure system affected the southern coast of Catalonia (NE Spain). The synoptic framework was dominated by an upper level trough and an associated cold front extending from Gibraltar along the Mediterranean coast of the Iberian Peninsula to SE France, which moved north-eastward. South easterly winds in the north of the Balearic Islands and the coast of Catalonia favoured high values of 0-3 km storm relative helicity which combined with moderate MLCAPE values and high shear favoured the conditions for organized convection. A number of multicell storms and others exhibiting supercell features, as indicated by Doppler radar observations, clustered later in a mesoscale convective system, and moved north-eastwards across Catalonia. They produced ground-level strong damaging wind gusts, an F2 tornado, hail and heavy rainfall. Total lightning activity (intra-cloud and cloud to ground flashes) was also relevant, exhibiting several classical features such as a sudden increased rate before ground level severe damage, as discussed in a companion study. Remarkable surface observations of this event include 24 h precipitation accumulations exceeding 100 mm in four different observatories and 30 minute rainfall amounts up to 40 mm which caused local flash floods. As the convective system evolved northward later that day it also affected SE France causing large hail, ground level damaging wind gusts and heavy rainfall.

  17. 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.

  18. X-band Polarimetric Radar Rainfall Measurements in Keys Area Microphysics Project.

    NASA Astrophysics Data System (ADS)

    Anagnostou, Emmanouil N.; Grecu, Mircea; Anagnostou, Marios N.

    2006-01-01

    The Keys Area Microphysics Project (KAMP), conducted as part of NASA’s Fourth Convective and Moisture Experiment (CAMEX-4) in the lower Keys area, deployed a number of ground radars and four arrays of rain gauge and disdrometer clusters. Among the various instruments is an X-band dual-polarization Doppler radar on wheels (XPOL), contributed by the University of Connecticut. XPOL was used to retrieve rainfall rate and raindrop size distribution (DSD) parameters to be used in support of KAMP science objectives. This paper presents the XPOL measurements in KAMP and the algorithm developed for attenuation correction and estimation of DSD model parameters. XPOL observations include the horizontal polarization reflectivity ZH, differential reflectivity ZDR, and differential phase shift DP. Here, ZH and ZDR were determined to be positively biased by 3 and 0.3 dB, respectively. A technique was also applied to filter noise and correct for potential phase folding in DP profiles. The XPOL attenuation correction uses parameterizations that relate the path-integrated specific (differential) attenuation along a radar ray to the filtered-DP (specific attenuation) profile. Attenuation-corrected ZH and specific differential phase shift (derived from filtered DP profiles) data are then used to derive two parameters of the normalized gamma DSD model, that is, intercept (Nw) and mean drop diameter (D0). The third parameter (shape parameter ?) is calculated using a constrained ? relationship derived from the measured raindrop spectra. The XPOL attenuation correction is evaluated using coincidental nonattenuated reflectivity fields from the Key West Weather Surveillance Radar-1988 Doppler (WSR-88D), while the DSD parameter retrievals are statistically assessed using DSD parameters calculated from the measured raindrop spectra. Statistics show that XPOL DSD parameter estimation is consistent with independent observations. XPOL estimates of water content and Nw are also shown to be consistent with corresponding retrievals from matched ER-2 Doppler radar (EDOP) profiling observations from the 19 September airborne campaign. Results shown in this paper strengthen the applicability of X-band dual-polarization high resolution observations in cloud modeling and precipitation remote sensing studies.

  19. A space-time multifractal analysis on radar rainfall sequences from central Poland

    NASA Astrophysics Data System (ADS)

    Licznar, Pawe?; Deidda, Roberto

    2014-05-01

    Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal analysis is carried out assuming Taylor's hypothesis to hold and the advection velocity needed to rescale the time dimension is assumed to be equal about 16 km/h. This assumption is verified by the analysis of autocorrelation functions along the x and y directions of "rainfall cubes" and along the time axis rescaled with assumed advection velocity. In general for analyzed rainfall sequences scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. However in most cases scaling break is identified for spatial scales between 4 and 8, corresponding to spatial dimensions of 16 km to 32 km. It is assumed that the scaling break occurrence at these particular scales in central Poland conditions could be at least partly explained by the rainfall mesoscale gap (on the edge of meso-gamma, storm-scale and meso-beta scale).

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. Estimation of areal rainfall using the radar echo area time integral

    NASA Technical Reports Server (NTRS)

    Lopez, Raul E.; Blanchard, David O.; Atlas, David; Rosenfeld, Daniel; Thomas, Jack L.

    1989-01-01

    The Area Time Integral (ATI) method of Doneaud et al. (1984) is extended to the measurement of cumulative areawide rainfall for periods up to 12 h. The extended ATI method is used to analyze data from the Florida Area Cumulus Experiment II. The relationship between radar estimated rain volume and radar-measured area covered with echoes is examined to test the possibility of obtaining values similar to conventional reflectivity-rainfall estimates of rainfall using only area measurements. The correlation between gage-estimated rain volume and radar estimated area covered with showers is also studied, focusing on the possible estimation of rain volume values using a small number of echo area observations.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Radar studies of heavy convective rainfall in mountainous terrain

    NASA Astrophysics Data System (ADS)

    Landel, Gregoire; Smith, James A.; Baeck, Mary Lynn; Steiner, Matthias; Ogden, Fred L.

    1999-01-01

    Heavy rainfall, topography, storm motion, and storm evolution are closely linked for four storms that produced catastrophic flooding along the Front Range of the Rocky Mountains and the east slope of the Blue Ridge Mountains. Storms selected for detailed study in this paper are the Rapidan storm of June 27, 1995, the Fort Collins storm of July 28, 1997, the Buffalo Creek storm of July 12, 1996, and the Monocacy storm of June 18, 1996. The Buffalo Creek storm and the Fort Collins storm occurred in the Front Range of the Rocky Mountains in Colorado; the Rapidan and Monocacy storms occurred along the east slopes of the Blue Ridge of Virginia and southern Pennsylvania. The four storms caused catastrophic flooding at drainage basin scales between 1 and 1000 km2. The scale of flood response for these events imposes a need to characterize rainfall variability at very fine space scales and timescales, of the order of 1 km spatial scale and 1-5 min timescale. A fundamental issue for the hydrometeorology of extreme rainfall in mountainous terrain is whether anomalously large rainfall accumulations in orographic convection result from anomalously slow net storm motion, anomalously large rainfall rates, or both. Anomalous storm motion and processes resulting in catastrophic rainfall rates are examined for each of the four storms. Of particular importance for anomalous storm motion in orographic convection are interactions between the low-level wind field and terrain features.

  12. Experiments in Rainfall Estimation with a Polarimetric Radar in a Subtropical Environment.

    NASA Astrophysics Data System (ADS)

    Brandes, Edward A.; Zhang, Guifu; Vivekanandan, J.

    2002-06-01

    A unique dataset consisting of high-resolution polarimetric radar measurements and dense rain gauge and disdrometer observations collected in east-central Florida during the summer of 1998 was examined. Comparison of the radar measurements and radar parameters computed from the disdrometer observations supported previous studies, which indicate that oscillating drops in the free atmosphere have more spherical apparent shapes in the mean than equilibrium shapes. Radar-disdrometer comparisons improved markedly when using an empirical axis ratio relation developed from observational studies and representing more spherical drop shapes. Fixed-form power-law rainfall estimators for radar reflectivity (ZH), specific differential phase (KDP), specific differential phase-differential reflectivity (KDP, ZDR), and radar reflectivity-differential reflectivity (ZH, ZDR) were then determined using the disdrometer observations. Relations were produced for both equilibrium shapes and the empirical axis ratios. Polarimetric rainfall estimators based on more spherical shapes gave significantly improved performance. However, the improvement was largely in bias mitigation. Rainfall estimates with the ZH-ZDR measurement pair had the highest correlation with rain gauge observations, the smallest range in bias factors from storm to storm, and the smallest root-mean-square error.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Disdrometer measurements during a unique rainfall event in central Illinois and their implication for differential reflectivity radar observations

    NASA Technical Reports Server (NTRS)

    Seliga, T. A.; Aydin, K.; Direskeneli, H.

    1983-01-01

    Understanding of the natural variability of rainfall is essential in order to assess radar's ability to estimate rainfall characteristics such as rainfall rate, rainfall water content and drop size distribution parameters. The two most useful measurements of rainfall for this purpose derive from ground-based disdrometers and aircraft-borne drop size spectrometers. Accordingly, this paper examines a time series of disdrometer measurements obtained during a unique rainfall event which occurred in central Illinois on October 6, 1982. The measurements are used to predict the behavior of radar observables (reflectivity factor and differential reflectivity) for application to the estimation of rainfall parameters. The results support previous theoretical predictions (Seliga and Bringi, 1976) and experimental results (Seliga et al., 1979, 1981; Bringi et al., 1982; Hall et al., 1980; Goddard et al., 1982) based upon the differential reflectivity (ZDR) radar technique.

  19. Analyses of a long-term, high-resolution radar rainfall data set for the Baltimore metropolitan region

    NASA Astrophysics Data System (ADS)

    Smith, James A.; Baeck, Mary Lynn; Villarini, Gabriele; Welty, Claire; Miller, Andrew J.; Krajewski, Witold F.

    2012-04-01

    We introduce a long-term, high-resolution radar rainfall data set for the Baltimore metropolitan area covering the 10-yr period from 2000-2009. Rainfall fields are developed at 15 min time interval and 1 km horizontal resolution for a 17,000-km2 region centered on the Baltimore metropolitan area. The Hydro-NEXRAD system is used as a platform for generating radar rainfall fields. We utilize the high-resolution, 10-yr data set to characterize striking spatial heterogeneities in rainfall for the Baltimore metropolitan region, both in terms of mean rainfall and rainfall extremes. The role of complex terrain (associated with urbanization, the Chesapeake Bay, and mountainous terrain) in controlling spatial heterogeneities of rainfall climatology for the Baltimore study region is discussed. We also characterize the seasonal and diurnal variation of rainfall over the study region using the 10-yr rainfall data set, with particular focus on the diurnal variation of rainfall during the warm season. High-resolution rainfall fields are especially useful for examining the distribution of rainfall from a drainage basin perspective, as illustrated through analyses of basin-averaged rainfall rate for basins of contrasting drainage area and analyses of the duration of dry periods for small urban watersheds. Analyses and methodologies used to develop the long-term Baltimore rainfall data set are broadly applicable to other regions of the United States and in settings around the world with long-term, high-quality radar data sets.

  20. 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.

  1. 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.

  2. 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-? 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-? gram, CAPE.

  3. An Analytical Solution for Raindrop Evaporation and Its Application to Radar Rainfall Measurements.

    NASA Astrophysics Data System (ADS)

    Li, Xiaowen; Srivastava, Ramesh C.

    2001-09-01

    An analytical solution for the evaporation of a single raindrop is derived in this paper. Based on this solution, a parameter D( is defined as the diameter of the raindrop that just evaporates completely after falling through a certain distance in a prescribed environment. The parameter D( is then used for studying the modification of raindrop size distribution by evaporation in a steady, still atmosphere. The results for the Marshall-Palmer distribution are used to discuss errors caused by rain evaporation in radar rainfall measurements. Quantitative estimation of these errors, or as an equivalent, estimation of the rain evaporation along the falling path, using both radar reflectivity Z and radar differential reflectivity ZDR techniques, is studied. The results show that, for the detection of rain evaporation, reflectivity is more sensitive than differential reflectivity, whereas for the estimation of rainfall rate R, an empirical ZDR-Z-R formula is more robust and accurate than a Z-R formula.

  4. 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.

  5. Multifunction millimetre-wave radar for all-weather ground attack aircraft

    NASA Astrophysics Data System (ADS)

    Potter, K. E.

    1986-07-01

    Details of the millimeter wave radar performance are presented which show that with potentially available power sources an all weather capability can be realized. Performance is evaluated as a function of frequency and antenna size, and the use of polarimetry with wide bandwidth/coherent processing is shown to offer potential enhancement for target discrimination. The millimeter wave radar is shown to be potentially capable of satisfying the following functions: take off/landing, terrain following, area correlation, tercom, and acquisition of targets. The above roles can be achieved in an all weather environment making the millimeter wave radar a valuable multifunction airborne radar.

  6. On the simulation of infiltration- and saturation-excess runoff using radar-based rainfall estimates: Effects of algorithm uncertainty and pixel aggregation

    NASA Astrophysics Data System (ADS)

    Winchell, Michael; Gupta, Hoshin Vijai; Sorooshian, Soroosh

    1998-10-01

    The effects of uncertainty in radar-estimated precipitation input on simulated runoff generation from a medium-sized (100-km2) basin in northern Texas are investigated. The radar-estimated rainfall was derived from Next Generation Weather Radar (NEXRAD) Level II base reflectivity data and was supplemented by ground-based rain-gauge data. Two types of uncertainty in the precipitation estimates are considered: (1) those arising from the transformation of reflectivity to rainfall rate and (2) those due to the spatial and temporal representation of the "true" rainfall field. The study explicitly differentiates between the response of simulated saturation-excess runoff and infiltration-excess runoff to these uncertainties. The results indicate that infiltration-excess runoff generation is much more sensitive than saturation-excess runoff generation to both types of precipitation uncertainty. Furthermore, significant reductions in infiltration-excess runoff volume occur when the temporal and spatial resolution of the precipitation input is decreased. A method is developed to relate this storm-dependent reduction in runoff volume to the spatial heterogeneity of the highest-intensity rainfall periods during a storm.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Quality-based generation of weather radar Cartesian products

    NASA Astrophysics Data System (ADS)

    O?ródka, K.; Szturc, J.

    2014-11-01

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

  12. Microphysical variability of tropical and mid-latitude rainfall as revealed by polarimetric radar

    NASA Astrophysics Data System (ADS)

    Rutledge, S. A.; Dolan, B.; Chandrasekar, C. V.; Kennedy, P.; Wolff, D. B.; Petersen, W. A.

    2013-12-01

    Gorgucci et al. (2006) showed that a parameter space defined by several polarimetric radar variables could be used to characterize the shape of raindrops. This study has been extended using the so-called self-consistency analysis to identify rainfall regimes, specifically warm rain coalescence compared to the melting of large ice particles that have grown by riming. For a given rainfall regime, the behavior of Kdp/Z (where Kdp is the specific differential phase and Z is the linear reflectivity) plotted against Zdr (differential reflectivity) in rain-only regions is useful in identifying precipitation physics. Kdp is proportional to water mass content and mass-weighted oblateness ratio, whereas Zdr is a measure of particle oblateness of the largest drops in a sample volume. Z is proportional to concentration and diameter. Using data from polarimetric radar observations at several places (both tropical and mid-latitude) around the globe we demonstrate microphysical variability in rainfall associated with intraseasonal variability, differences in organization (isolated convection vs. organized), and regional variability. Several of these datasets have resulted from TRMM and GPM field campaigns, including the Mid-Latitude Continental Convective Clouds Experiment (MC3E) and Iowa Flood Studies (IFloodS). Implications for Z-based rain estimation as used by the TRMM and GPM precipitation radars will be discussed. This technique could also be applied to the nation's NEXRAD WSR-88DP data to better understand the microphysical characteristics of rainfall across the U.S.

  13. 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.

  14. Comparison of Spatial and Temporal Rainfall Characteristics of WRF-Simulated Precipitation to gauge and radar observations

    NASA Astrophysics Data System (ADS)

    Price, K.; Purucker, T.; Andersen, T. K.; Knightes, C. D.; Cooter, E. J.; Otte, T.

    2012-12-01

    Weather Research and Forecasting (WRF) meteorological data are used for US EPA 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 hindcasting applications of WRF simulations match observed rainfall on a day-to-day or individual event basis, it is important that the overall spatio-temporal structure of precipitation events represents reality. It has been shown that contaminant fate-and-transport is strongly event-dependent, and the temporal structure of precipitation (and subsequent streamflows) is a major driver of instream flows relating to habitat suitability, contaminant fluxes, dilution, water supply, etc. The spatial and temporal variability of WRF-simulations in the North Carolina Piedmont and Coastal Plain was compared to two observed precipitation datasets, interpolated National Climate Data Center (NCDC) gauge and Multisensor Precipitation Estimate (MPE) radar data. NCDC data are point data comprised of rain-gauge observations, which we interpolated to the 12 km WRF grid using co-kriging (with elevation as the covariate). MPE data, also known as Stage IV NEXRAD, are Doppler-radar derived, HADS-adjusted rainfall estimates at a 4 km resolution, which we resampled to match the 12 km WRF grid. Variographic properties were used to compare spatial structure of rainfall across daily, monthly, seasonal, and annual rainfall totals during the five-year study period. In addition, the variography of a sample of storm events stratified by intensity and type (e.g., frontal , local convective, and tropical cyclones) was compared. Three-way ANOVA was used to compare variographic parameters across the datasets. Temporal structure was compared using partial autocorrelation functions and seasonal decompositions. Evaluation of modeled precipitation spatial and temporal structure, as compared with two observed datasets, allows insights into errors that propagate through stages of water quality, future scenarios, etc. when using WRF simulations. These results will guide future improvements to WRF simulations used within the EPA air and water modeling programs. These results also demonstrate differences in the spatio-temporal structure of the two observed precipitation datasets and provides guidance for use of gauge and radar precipitation data in hindcasting modeling efforts for understanding watershed function and process.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

    2015-02-01

    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.

  3. 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.

  4. Detection of convective cells with a potential to produce local heavy rainfalls by a C-band polarimetric radar

    NASA Astrophysics Data System (ADS)

    Adachi, Ahoro; Kobayashi, Takahisa; Yamauchi, Hiroshi; Onogi, Shigeru

    2011-11-01

    Recent studies have shown that polarimetric radars are capable of providing distributions of rain intensity with high accuracy. Variables obtained by the polarimetric radars include radar reflectivity factor (Zhh), differential propagation phase (?dp) and differential reflectivity (Zdr). A number of methods to estimate rain intensity from these variables have been proposed. In this study, the rain intensity estimated from the differential reflectivity and radar reflectivity factor measured with a C-band polarimetric radar is used to analyze a local heavy rainfall event as a case study because the differential reflectivity measured with C-band radar is more sensitive to large raindrops associated with heavy rainfalls than is radars operating at other frequencies. Results show that the estimated rainfall intensity agrees well with surface observations made during the event. Moreover, the so-called high Zdr column, a large differential reflectivity region was clearly analyzed aloft about 10 minutes prior to the local heavy rainfall on the ground, suggesting that the differential reflectivity observed with C-band polarimetric radar can be a good index to detect heavy precipitation events in advance.

  5. 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.

  6. 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.

  7. Reliability and robustness of rainfall compound distribution model based on weather pattern sub-sampling

    NASA Astrophysics Data System (ADS)

    Garavaglia, F.; Lang, M.; Paquet, E.; Gailhard, J.; Garçon, R.; Renard, B.

    2010-09-01

    Design floods for EDF (Électricité de France, French electricity company) dam spillways are now computed using a probabilistic method named SCHADEX (Climatic-Hydrological Simulation of Extreme Floods) based on an extreme rainfall model named the MEWP (Multi Exponential Weather Pattern) distribution. This probabilistic model provides estimates of extreme rainfall quantiles using a mixture of exponential distributions. Each exponential distribution applies to a specific sub-sample of rainfall observations, corresponding to one of eight typical atmospheric circulation patterns that are relevant for France and the surrounding area. The aim of this paper is to validate the MEWP model by assessing its reliability and robustness with rainfall data from France, Spain and Switzerland. Data include 37 long series for the period 1904-2003, and a regional data set of 478 rain gauges for the period 1954-2005. Two complementary properties are investigated: (i) the reliability of estimates, i.e. the agreement between the estimated probabilities of exceedance and the actual exceedances observed on the dataset; (ii) the robustness of extreme quantiles and associated confidence intervals, assessed using various sub-samples of the long data series. New specific criteria are proposed to quantify reliability and robustness.The MEWP model is compared to standard models (seasonalised Generalised Extreme Value and Generalised Pareto distributions). In order to evaluate the suitability of the exponential model used for each weather pattern (WP), a general case of the MEWP distribution, using Generalized Pareto distributions for each WP, is also considered. Concerning the considered dataset, the exponential hypothesis of asymptotic behaviour of each seasonal and weather pattern rainfall records, appears to be reasonable. The results highlight: (i) the interest of WP sub-sampling that lead to significant improvement in reliability models performances; (ii) the low level of robustness of the models based on at-site estimation of shape parameter; (iii) the MEWP distribution proved to be robust and reliable, demonstrating the interest of the proposed approach.

  8. 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.

  9. 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.

  10. 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.

  11. Dual polarization radar rainfall estimation using the mean linear raindrop shape model

    NASA Astrophysics Data System (ADS)

    Gorgucci, E.; Baldini, L.; Romaniello, V.

    2009-04-01

    Information about the shape of raindrops is critical for estimating rainfall rate with dual polarization radar. As described in the literature, the relation describing drop oblateness as a function of its equivolumetric diameter is nonlinear. In fact, there is still no consensus regarding the most appropriate equation to use to describe the shape-size relation. However, while these non-linear equations are important for studying raindrop shape, it is not clear whether they are needed to estimate an integral quantity such as rainfall rate. A rain algorithm using Zh, and Zdr and an equivalent linear shape-size model with variable slope (?) that can be determined from an equation relating it to Zh, Zdr, and Kdp measurements is analyzed. To test its performance realistic rain and radar measurement profiles reconstructed from real radar observations were used. Starting from radar profiles collected by the NCAR S-POL dual polarization radar, two different sets of radar profiles were obtained for S-, C-, and X-band assuming the raindrop shape-size relations of Pruppacher and Beard (1970) and Beard and Chuang (1986). The first model is linear and the second is a non-linear one, expressed by a fourth order polynomial. The performance of the proposed rain algorithms based on ? is compared with that of algorithms derived assuming two drop shape relations expressed by a fourth order polynomial recently proposed. The simulation procedure allows the study of the influence of DSD variability as well as the effect of measurement errors on rain rate estimations. In general, it is possible to conclude that the rain algorithm based on an equivalent linear shape-size model performs better than the THBRS and BZV algorithms, since in worst cases, the performance of the ? algorithm is not too far from the performance of the standard rain algorithm obtained assuming the two non-linear shape size relations. In summary, although the literature indicates that the relation between oblateness and diameter of raindrops can be appropriately described by a nonlinear relation, the exact knowledge of this relation is not necessary in the case of estimation of an integral quantity such as the rainfall rate. Is fact, using a simple equivalent linear shape-size model can be convenient to obtain reliable estimations.

  12. High resolution measurements of aerial rainfall with X-band radars in New Zealand

    NASA Astrophysics Data System (ADS)

    Sutherland-Stacey, Luke; Shucksmith, Paul; Austin, Geoff

    2010-05-01

    The Atmospheric Physics Group runs a number of high resolution X-band mobile rain radars. The radars are unusual in that they operate at very high spatial and temporal resolution but short range (100m/20sec/20km) as compared with the C-band radars of the New Zealand Meteorological Service (2km/7min/240km). Portability was a key design criterion for the radars, which can either be towed by a personal four wheel drive vehicle or carted by a container truck. Past deployments include the slopes of an erupting volcano, the path of a tropical storm and overwintering in a mountain range. It is well known that sampling and representativeness problems associated with sparse gauge networks and C-band radars can result in high uncertainty in estimates of aerial rainfall. Some of this error is associated with poor sampling of the spatial and temporal scales which are important to precipitation processes. In the case of long range radar, the beam height increase with range also introduces uncertainty when trying to infer precipitation at the ground, even after reflectivity profile correction methods are applied. This paper describes a recently completed field campaign in a hydro power catchment in the North Island of New Zealand. The radar was deployed in a pasture on a farm overlooking the catchment which is about 15km x 10km in size. The catchment is about 150km from the nearest national C-band radar. A number of rain gauges, including high resolution drop counters, were deployed nearby. X-band and comparative C-band radar observations of particular events including orographically initiated convection, frontal systems and widespread rain types are presented. The convective events are characterised by short length scales and rapid evolution, but even the widespread rain has embedded structure. The observations indicate that the evolution time and spatial scales associated with many of the hydrometeors observed in this work precludes aerial estimates being made with sparse gauge networks. Due to the relatively long range and lower spatial and temporal resolution the C-band images contained less information than X-band scans of the same hydrometeors. On the other hand, per event statistics indicate that the majority of variance in rain gauge measurements can be explained from the co-located X-band radar pixel. Quantitative retrieval of accumulation was possible out to about 15km range after applying range and bias correction.

  13. The operational weather radar of Fossalon di Grado (Gorizia, Italy): accuracy of reflectivity and differential reflectivity measurements

    NASA Astrophysics Data System (ADS)

    Bechini, R.; Gorgucci, E.; Scarchilli, G.; Dietrich, S.

    The error structure of radar measurements should be accurately known in order to provide reliable estimates for a number of quantitative meteorological applications, from rainfall rate estimation to cloud microphysics. The aim of this paper is to give a detailed characterization of ZH and ZDR measurements obtained by the weather radar of Fossalon di Grado (Gorizia, Italy). Vertical-looking observations are used to determine the system bias on differential reflectivity and to estimate the measurement error on both ZH and ZDR in the rain medium. It is estimated that no bias is affecting ZDR and the accuracy of ZH and ZDR is 0.8 and 0.1dB, respectively. A similar evaluation is done in the rain medium at larger ranges with the antenna pointing at low elevation angles. The long time stability of the absolute reflectivity calibration is also established by radar-rain gage inter-comparison over almost 200 hours of precipitation data collected during nearly two years.

  14. 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.

  15. 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 (? = 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.

  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 5×5 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. Rainfall Downscaling by a Phase-Conserving, Nonlinearly-Transformed Autoregressive Model: Validation on Radar Precipitation Estimates

    NASA Astrophysics Data System (ADS)

    Rebora, N.; Ferraris, L.; von Hardenberg, J.; Provenzale, A.

    2004-05-01

    The prediction of the small-scale spatio-temporal pattern of intense rainfall events is crucial for flood risk assessment in small catchments and urban areas. In the absence of a full deterministic modelling of small-scale rainfall, it is common practice to resort to the use of stochastic downscaling models to generate ensemble rainfall predictions to be used as inputs to rainfall-runoff models. Here we discuss a spatio-temporal downscaling procedure that we call the "Rain FARM: Rainfall Filtered AutoRegressive Model," based on a non-linear transformation of a linearly correlated (gaussian) field, and we validate this approach on a set of radar precipitation estimates. The Rain FARM procedure allows for reproducing the scaling properties (if any) of the rainfall pattern and it can be easily linked with meteorological forecasts produced by limited area meteorological models. We believe that this approach represents a significant improvement over commonly available models used for rainfall downscaling.

  19. 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.

  20. 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.

  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. Simultaneous ocean cross section and rainfall measurements from space with a nadir-looking radar

    NASA Technical Reports Server (NTRS)

    Meneghini, Robert; Atlas, David

    1986-01-01

    In the case of a nadir-looking spaceborne or aircraft radar in the presence of rain, the return power corresponding to secondary surface scattering may provide information on the properties of the surface and the precipitation. The object of the study is to evaluate a method for determining simultaneously the rainfall rate and the backscattering coefficient of the surface. The method is based upon the mirror-reflected power, which corresponds to the portion of the incident power scattered from the surface to the precipitation, intercepted by the precipitation, and again returned to the surface where it is scattered a final time back to the antenna.

  3. 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

  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. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Were global numerical weather prediction systems capable of forecasting the extreme Colorado rainfall of 9-16 September 2013?

    NASA Astrophysics Data System (ADS)

    Lavers, David A.; Villarini, Gabriele

    2013-12-01

    9-16 September 2013 significant portions of Colorado experienced extreme precipitation and flooding resulting in large socioeconomic damages and fatalities. Here we investigate the ability of eight global state-of-the-art numerical weather prediction systems to forecast rainfall during the event. Forecasts were analyzed from initializations at 12 UTC 5 September to 12 UTC 12 September to determine when, and how well, the event was captured. Ensemble mean rainfall patterns initialized on 5 September (roughly 4+ day lead time) did not forecast the event's persistent nature; conversely, forecasts initialized on 9 September captured the rainfall patterns reasonably well, although with incorrect rainfall values. Accumulated rainfall forecasts improved when the region considered increased from a 0.5° area centered over Boulder to the entire state of Colorado. We conclude that the models provided guidance indicating a significant period of rainfall in Colorado from 9 September 2013, although not necessarily in the correct locations.

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

    PubMed

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

    2003-09-15

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

  17. 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.

  18. 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.

  19. 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.

  20. 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 (? (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 ? (R)/R into a qualitative uncertainty index (UI) ranging from 1 to 5, where 1 is very certain and 5 is very uncertain.

  1. 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.

  2. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

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

    NASA Astrophysics Data System (ADS)

    Tho Dang, Van; Yanovsky, F. J.

    2009-06-01

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

  5. 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.

  6. Passive Microwave Rainfall Error Analysis using High-Resolution X-band Dual-Polarization Radar Observations in Complex Terrain

    NASA Astrophysics Data System (ADS)

    Derin, Yagmur; Anagnostou, Emmanouil; Kalogiros, John; Anagnostou, Marios

    2015-04-01

    Accuracy and reliability of hydrological modeling studies heavily depends on quality and availability of precipitation estimates. Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements, such as those obtained during experimental studies with research radars. This study evaluates rainfall estimates from passive microwave (PMW) sensors onboard different earth orbiting platforms based on high spatial (150 m) and temporal (3 min) resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations during various field experiments in US and the Mediterranean region. The study first conducts independent error analysis of the XPOL precipitation estimates using independent in situ observations from rain gauges and disdrometers. Subsequently, coincident XPOL and PMW rainfall estimates are matched in space and time for a number of convective and stratiform type precipitation events. Standard GPROF PMW retrievals on SSM/I, TMI (2A12) and GPM-DPR observations are used to conduct the error analysis. All coincident XPOL data are extracted for the indicated overpasses to produce the satellite field-of-view averages for the orbital PMW sensor and produce match-ups of PMW/XPOL rainfall and raindrop size distribution parameters. In addition, gridded merged PMW datasets (MWCOMB, 3B40RT) that are used in most merged rainfall products are evaluated against the XPOL measurements. We will present error analysis results of PMW rainfall estimation and investigate dependences on precipitation type, vertical structure and precipitation microphysics (derived from XPOL).

  7. On differentiating ground clutter and insect echoes from Doppler weather radars using archived data

    NASA Astrophysics Data System (ADS)

    Rennie, S. J.; Illingworth, A. J.; Dance, S. L.

    2010-04-01

    Normally wind measurements from Doppler radars rely on the presence of rain. During fine weather, insects become a potential radar target for wind measurement. However, it is difficult to separate ground clutter and insect echoes when spectral or polarimetric methods are not available. Archived reflectivity and velocity data from repeated scans provide alternative methods. The probability of detection (POD) method, which maps areas with a persistent signal as ground clutter, is ineffective when most scans also contain persistent insect echoes. We developed a clutter detection method which maps the standard deviation of velocity (SDV) over a large number of scans, and can differentiate insects and ground clutter close to the radar. Beyond the range of persistent insect echoes, the POD method more thoroughly removes ground clutter. A new, pseudo-probability clutter map was created by combining the POD and SDV maps. The new map optimised ground clutter detection without removing insect echoes.

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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

  14. 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…

  15. 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…

  16. 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.

  17. Application of Radar-Rainfall Estimates to Probable Maximum Precipitation in the Carolinas

    NASA Astrophysics Data System (ADS)

    England, J. F.; Caldwell, R. J.; Sankovich, V.

    2011-12-01

    Extreme storm rainfall data are essential in the assessment of potential impacts on design precipitation amounts, which are used in flood design criteria for dams and nuclear power plants. Probable Maximum Precipitation (PMP) from National Weather Service Hydrometeorological Report 51 (HMR51) is currently used for design rainfall estimates in the eastern U.S. The extreme storm database associated with the report has not been updated since the early 1970s. In the past several decades, several extreme precipitation events have occurred that have the potential to alter the PMP values, particularly across the Southeast United States (e.g., Hurricane Floyd 1999). Unfortunately, these and other large precipitation-producing storms have not been analyzed with the detail required for application in design studies. This study focuses on warm-season tropical cyclones (TCs) in the Carolinas, as these systems are the critical maximum rainfall mechanisms in the region. The goal is to discern if recent tropical events may have reached or exceeded current PMP values. We have analyzed 10 storms using modern datasets and methodologies that provide enhanced spatial and temporal resolution relative to point measurements used in past studies. Specifically, hourly multisensor precipitation reanalysis (MPR) data are used to estimate storm total precipitation accumulations at various durations throughout each storm event. The accumulated grids serve as input to depth-area-duration calculations. Individual storms are then maximized using back-trajectories to determine source regions for moisture. The development of open source software has made this process time and resource efficient. Based on the current methodology, two of the ten storms analyzed have the potential to challenge HMR51 PMP values. Maximized depth-area curves for Hurricane Floyd indicate exceedance at 24- and 72-hour durations for large area sizes, while Hurricane Fran (1996) appears to exceed PMP at large area sizes for short-duration, 6-hour storms. Utilizing new methods and data, however, requires careful consideration of the potential limitations and caveats associated with the analysis and further evaluation of the newer storms within the context of historical storms from HMR51. Here, we provide a brief background on extreme rainfall in the Carolinas, along with an overview of the methods employed for converting MPR to depth-area relationships. Discussion of the issues and limitations, evaluation of the various techniques, and comparison to HMR51 storms and PMP values are also presented.

  18. Offshore next generation weather radar (NEXRAD) test and evaluation master plan (TEMP)

    NASA Astrophysics Data System (ADS)

    Martinez, Radame; Cranston, Robert; Porcello, John

    1995-01-01

    This document provides the test philosophy and approach for the Offshore Next Generation Weather Radar (NEXRAD) Test and Evaluation Master Plan (TEMP). The NEXRAD differs from the typical Federal Aviation Administration (FAA) weather radar acquisition in that it is jointly funded by the Department of Defense (DOD), the Department of Commerce (DOC), and the Department of Transportation (DOT). These three agencies chartered the Joint System Program Office (JSPO) to manage the NEXRAD development and subsequent test programs. JSPO has deployed 70 single-channel radar systems across the continental United States (CONUS). The FAA is deploying NEXRAD systems at non-CONUS (offshore) locations such as Alaska, Hawaii, and the Caribbean. The FAA Offshore NEXRAD will have a redundant configuration and a Remote Monitoring Subsystem (EMS). A total of 14 Offshore NEXRAD's will be procured under this acquisition: 3 in the Caribbean, 4 in Hawaii, and 7 in Alaska. Funding constraints will limit the acquisition to seven NEXRAD's in the 1994-1995 timeframe.

  19. 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.

  20. A raingage, radar and satellite simulation study of the estimation of convective rainfall by area-time integrals

    NASA Technical Reports Server (NTRS)

    Short, David A.; Rosenfeld, Daniel; Wolff, David B.; Atlas, David

    1989-01-01

    Correlations between area-averaged rainrates and the areal fraction of rainrates exceeding a preset threshold, F(T), are examined using data from a network of 22 raingages located within 120 km of the NOAA/Tropical Ocean-Global Atmosphere (TOGA) C-band meteorological radar at Darwin, Australia. The results show that the area averages of convective rainfall are highly correlated with the fraction F(T). To simulate the use of the relationship between area-averaged rainrates and F(T) to obtain space-time averaged rainrates from a satellite sensor, observations from the NOAA/TOGA radar observations are used to estimate F(T) using a reflectivity threshold. The use of area-time integral methods for inferring area-averaged rainrates from satellites is examined, noting the possible use of the methodology for the Tropical Rainfall Measuring Mission.

  1. 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.

  2. 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.

  3. Bias correction of satellite rainfall estimates using a radar-gauge product - a case study in Oklahoma (USA)

    NASA Astrophysics Data System (ADS)

    Tesfagiorgis, K.; Mahani, S. E.; Krakauer, N. Y.; Khanbilvardi, R.

    2011-08-01

    Hourly Satellite Precipitation Estimates (SPEs) may be the only available source of information for operational hydrologic and flash flood prediction due to spatial limitations of radar and gauge products. SPEs are prone to larger systematic errors and more uncertainty sources in comparison with ground based radar and gauge precipitation products. The present work develops an approach to seamlessly blend satellite, radar and gauge products to fill gaps in ground-based data. To mix different rainfall products, the bias of any of the products relative to each other should be removed. The study presents and tests a proposed ensemble-based method which aims to estimate spatially varying multiplicative biases in hourly SPEs using a radar-gauge rainfall product and compare it with previously used bias correction methods. Bias factors were calculated for a randomly selected sample of rainy pixels in the study area. Spatial fields of estimated bias were generated taking into account spatial variation and random errors in the sampled values. Bias field parameters were determined on a daily basis using the shuffled complex evolution optimization algorithm. To include more error sources, ensembles of bias factors were generated and applied before bias field generation. We demonstrate this method using two satellite-based products, CPC Morphing (CMORPH) and Hydro-Estimator (HE), and a radar-gauge rainfall Stage-IV (ST-IV) dataset for several rain events in 2006 over Oklahoma. The method was compared with 3 simpler methods for bias correction: mean ratio, maximum ratio and spatial interpolation without ensembles. Bias ratio, correlation coefficient, root mean square error and mean absolute difference are used to evaluate the performance of the different methods. Results show that: (a) the methods of maximum ratio and mean ratio performed variably and did not improve the overall correlation with the ST-IV in any of the rainy events; (b) the method of interpolation was consistently able to improve all the performance criteria; (c) the method of ensembles outperformed the other 3 methods.

  4. 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.

  5. 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

  6. Structure of precipitating systems over Taiwan’s complex terrain during Typhoon Morakot (2009) as revealed by weather radar and rain gauge observations

    NASA Astrophysics Data System (ADS)

    Liou, Yu-Chieng; Wang, Tai-Chi Chen; Tsai, Yi-Chun; Tang, Yu-Shuang; Lin, Pay-Liam; Lee, Yung-An

    2013-12-01

    This study documents from an observational perspective the structure of precipitation systems over the complex topography of Taiwan as Typhoon Morakot (2009) impinged on the island on 8 August 2009. An advanced multiple-Doppler radar synthesis technique particularly designed for dealing with non-flat surfaces is applied to analyze the three-dimensional wind fields over the ocean and terrain. In the northern and southern portion of the analysis domain where the mountain slope is relatively gentle and steep, respectively, the radar reflectivity measurements indicate that the precipitation systems exhibit very distinct features, namely, horizontal translation in the north and abrupt intensification in the south. While still far from the southern mountainous region, a north-south oscillation of an east-west-oriented band of strong radar reflectivity (>40 dBZ) with a horizontal span of 20 km is observed. Along the mountain slopes, the band of strong radar reflectivity has a much wider north-south extent. Both the radar and rain gauge observations show that the major precipitation is primarily confined to the windward side of the mountains. An analysis of the saturated Brunt-Väisälä frequency reveals that the upstream atmosphere is statically unstable, which implies that the lifting of the incoming convective cells by the topography will easily trigger precipitation. Thus, most of the moisture will be consumed before the air reaches the leeward side of the mountains. The long duration and the wide range of heavy precipitation in the mountainous regions resulted in a record-breaking average (over the gauges) rainfall amount of 2000 mm over 4 days. The prevailing winds approaching the mountains are from the west. The cross-barrier wind speed has a maximum (?40 m s-1) above the mountain crest that can be reasonably explained by a simplified shallow water model. The capability of applying the weather radar to provide a reliable quantitative estimate of the rainfall over a large area with high temporal and spatial resolution is demonstrated using dual-polarimetric radar data. The potential applications of the knowledge of the wind and precipitation characteristics in hydrology and other fields are addressed in this manuscript.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Proposed adopted environmental assessment for the next generation weather radar facility at Brookhaven National Laboratory

    SciTech Connect

    Not Available

    1992-06-01

    The US Department of Commerce (DOC) completed an environmental impact assessment review, under the National Environmental Policy Act (NEPA), on its decisions for the nationwide Next Generation Weather Radar (NEXRAD) program of 150 radar units and for the site specific assessments of impacts. The DOC published a Programmatic Enviornmental Impact Statement on NEXRAD in November 1984. It completed a site-specific Environmental Assessment (EA) on the proposed NEXRAD facility at DOE`s Brookhaven National Laboratory (BNL) in November 1991 and issued a Finding of No Significant Impact (FONSI) on March 12, 1992. The DOC EA is included. The Department of Energy (DOE) proposes to adopt, in its entirety, the November 1991 site-specific EA prepared by the DOC for construction and operation of the NEXRAD facility and a National Weather Service (NWS) office building at BNL. The DOE`s decision is whether or not to lease a tract of land on DOE property to the DOC for use by the NWS. The DOE has performed an an in-depth review of the DOC EA to verify its accuracy and completeness, and to ensure that it encompasses the environmental issues at BNL relevant to the DOE proposed action for lease of land to the DOC. The DOE, therefore, proposes to adopt the DOC EA in its entirety by preparation of this brief addendum to assess the impacts.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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).

  1. 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.

  2. 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.

  3. 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.

  4. Validation of satellite OPEMW precipitation product with ground-based weather radar and rain gauge networks

    NASA Astrophysics Data System (ADS)

    Cimini, D.; Romano, F.; Ricciardelli, E.; Di Paola, F.; Viggiano, M.; Marzano, F. S.; Colaiuda, V.; Picciotti, E.; Vulpiani, G.; Cuomo, V.

    2013-05-01

    The Precipitation Estimation at Microwave Frequencies (PEMW) algorithm was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) for inferring surface rain intensity (sri) from satellite passive microwave observations in the range from 89 to 190 GHz. The operational version of PEMW (OPEMW) has been running continuously at IMAA-CNR for two years, producing sri estimates feeding an operational hydrological model for forecasting flood alerts. This paper presents the validation of OPEMW against simultaneous ground-based observations obtained by a network of 20 weather radars and a network of more than 3000 rain gauges distributed over the Italian peninsula and main islands. The validation effort uses a data set spanning a one-year period (July 2011-June 2012). The effort evaluates dichotomous and continuous scores for the assessment of rain detection and quantitative estimate, respectively, investigating both spatial and temporal features. The analysis demonstrates 98% accuracy in correctly identifying rainy and non-rainy areas, and it quantifies the increased ability (with respect to random chance) to detect rainy and non-rainy areas (0.42-0.45 Heidke skill score) or rainy areas only (0.27-0.29 equitable threat score). Performances are better than average during summer, fall, and spring, while worse than average in the winter season. The spatial-temporal analysis does not show seasonal dependence except for larger mean absolute difference over the Alps and northern Apennines during winter, attributable to residual effect of snow cover. A binned analysis in the 0-15 mm h-1 range suggests that OPEMW tends to slightly overestimate sri values below 6-7 mm h-1, and to underestimate sri above those values. Depending upon the ground reference (either rain gauges or weather radars), the mean difference is 0.8-2.8 mm h-1, with a standard deviation within 2.6-3.1 mm h-1 and correlation coefficient within 0.8-0.9. The monthly mean difference was shown to remain within ±1 mm h-1 with respect to rain gauges and within -2 mm h-1 with respect to weather radars, with 2-4 mm h-1 standard deviation.

  5. Validation of satellite OPEMW precipitation product with ground-based weather radar and rain gauge networks

    NASA Astrophysics Data System (ADS)

    Cimini, D.; Romano, F.; Ricciardelli, E.; Di Paola, F.; Viggiano, M.; Marzano, F. S.; Colaiuda, V.; Picciotti, E.; Vulpiani, G.; Cuomo, V.

    2013-11-01

    The Precipitation Estimation at Microwave Frequencies (PEMW) algorithm was developed at the Institute of Methodologies for Environmental Analysis of the National Research Council of Italy (IMAA-CNR) for inferring surface rain intensity (sri) from satellite passive microwave observations in the range from 89 to 190 GHz. The operational version of PEMW (OPEMW) has been running continuously at IMAA-CNR for two years. The OPEMW sri estimates, together with other precipitation products, are used as input to an operational hydrological model for flood alert forecast. This paper presents the validation of OPEMW against simultaneous ground-based observations from a network of 20 weather radar systems and a network of more than 3000 rain gauges distributed over the Italian Peninsula and main islands. The validation effort uses a data set covering one year (July 2011-June 2012). The effort evaluates dichotomous and continuous scores for the assessment of rain detection and quantitative estimate, respectively, investigating both spatial and temporal features. The analysis demonstrates 98% accuracy in correctly identifying rainy and non-rainy areas; it also quantifies the increased ability (with respect to random chance) to detect rainy and non-rainy areas (0.42-0.45 Heidke skill score) or rainy areas only (0.27-0.29 equitable threat score). Performances are better than average during summer, fall, and spring, while worse than average in the winter season. The spatial-temporal analysis does not show seasonal dependence except over the Alps and northern Apennines during winter. A binned analysis in the 0-15 mm h-1 range suggests that OPEMW tends to slightly overestimate sri values below 6-7 mm h-1 and underestimate sri above those values. With respect to rain gauges (weather radars), the correlation coefficient is larger than 0.8 (0.9). The monthly mean difference and standard deviation remain within ±1 and 2 mm h-1 with respect to rain gauges (respectively -2-0 and 4 mm h-1 with respect to weather radars).

  6. 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…

  7. 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…

  8. 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.

  9. 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.

  10. Analysis of daily rainfall of the Sahelian weather-station Linguère (Senegal) - Trends and its impacts on the local population

    NASA Astrophysics Data System (ADS)

    Strommer, Gabriel; Brandt, Martin; Diongue-Niang, Aida; Samimi, Cyrus

    2013-04-01

    In the 20th century, the West African Sahel has been a hot-spot of climatic changes. After severe drought-events in the 1970s and 1980s which were followed by a significant drop in annual precipitation, rainfall seems to increase again during the past years. Most studies are based on monthly or yearly datasets. However, many processes and events which are important for the local population depending on rainfall are not related to monthly or annual precipitation but are related to intra-annual, often daily scales. During this study, interviews with farmers and herders were conducted in the Senegalese Sahel. The results show, that wet months with unsuitably distributed precipitation can cause more harm than bringing benefits - depending on the phenological stage of the plants. Agricultural crops for example need rainfall breaks. On the other hand, natural herbaceous vegetation tolerates longer wet periods. So, a wet season can still hide dry spells that alter crops and vegetation development. Based on the results of these interviews, this study developed two indexes, one for local farmers and one for herders separately, showing if the year was favorable for them or not. The indexes integrate the length of rainy seasons, intensity and frequency of rainfall events, breaks between events and also the previous year. This way, each year is assigned to one of 5 classes. Using daily rainfall data of the Linguère weather-station (from the Senegal Meteorological Service, ANACIM), trends of the indexes from 1945 to 2002 are detected and compared to results of the interviews. Statistically relating the indexes to yearly and monthly data demonstrates, how much information can be gathered by those datasets. Furthermore, changes in intensity and frequency are related with yearly and monthly sums showing relations between daily data and annual sums. For example, a high correlation (r=0.73) between the amount of rain days (> 1 mm) and the annual rainfall is observed in Linguère.

  11. The four cumulus cloud modes and their progression during rainfall events: A C-band polarimetric radar perspective

    NASA Astrophysics Data System (ADS)

    Kumar, Vickal V.; Jakob, Christian; Protat, Alain; May, Peter T.; Davies, Laura

    2013-08-01

    There is no objective definition to separate cumulus congestus clouds from the shallow cumulus and deep clouds. This has generated misinterpretation about the role of congestus clouds to promote deep convection through the potential of moistening the middle troposphere. In this study, an objective identification for the different tropical cumulus modes is found by examining the occurrence frequency of the cloud cell top heights (CTHs) and near-ground (at 2.5 km height) rainfall properties of these cells using a three-season database of the Darwin C-band polarimetric radar. Four cumulus modes were identified, namely a shallow cumulus mode with CTH in the trade inversion layer (1-3 km), a congestus mode with tops in the highly stable middle troposphere (3-6.5 km), a deep convective mode with tops in the region of free convection (6.5-15 km), and an overshooting convection mode with tops in the tropical tropopause layer (CTH >15 km). The study also investigates the connections between these cumulus modes during heavy rainfall events. The congestus mode occurs predominantly from ~10 h prior to the peak rainfall event to ~2 h past the event. The deep cloud populations (Modes 3 and 4) have their maxima at and shortly after the time of the rainfall peak, with maximum occurrence just below the tropical tropopause layer. A comparison of the heavy rainfall events occurring in morning (oceanic) conditions against the afternoon (continental) conditions revealed a higher ratio of the shallow to the deep cloud population and a shorter transition time from the shallow to the onset of deep population in the morning-oceanic conditions than the afternoon-land conditions. It is also found through the analysis of the large-scale moisture budget data set that for both the morning and afternoon events, the moistening peaked before the peak in the congestus populations.

  12. 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.

  13. 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.

  14. Simultaneous ocean cross-section and rainfall measurements from space with a nadir pointing radar

    NASA Technical Reports Server (NTRS)

    Atlas, D.; Meneghini, R.

    1983-01-01

    A modified version of the surface-target-attenuation radar described by Meneghini et al. (1983) is proposed which permits simultaneous measurement of ocean radar cross sections and path-average rain rates using a nadir-pointing satellite-borne microwave radar. The basic concept is explained and illustrated; the equations describing the data reduction are derived; some preliminary numerical computations based on a 7.5-m-diameter 10-kW 1.33-microsec-pulse radar operating at 1.87 cm from an altitude of 500 km are performed; and the major error sources (mismatches between rain scattering volumes and additional multipath contributions) and limitations (nadir pointing) are discussed. It is suggested that the system could provide a nadir calibration for wide-swath observing systems such as scanning microwave radiometers.

  15. Preliminary evaluation of polarimetric parameters from a new dual-polarization C-band weather radar in an alpine region

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

    The first operational weather radar with dual polarization capabilities was recently installed in Austria. The use of polarimetric radar variables rises several expectations: an increased accuracy of the rain rate estimation compared to standard Z-R relationships, a reliable use of attenuation correction methods, and finally hydrometeor classification. In this study the polarimetric variables of precipitation events are investigated and the operational quality of the parameters is discussed. For the new weather radar also several polarimetric rain rate estimators, which are based on the horizontal polarization radar reflectivity, ZH, the differential reflectivity, ZDR, and the specific differential propagation phase shift, KDP, have been tested. The rain rate estimators are further combined with an attenuation correction scheme. A comparison between radar and rain gauge indicates that ZDR based rain rate algorithms show an improvement over the traditional Z-R estimate. KDP based estimates do not provide reliable results, mainly due to the fact, that the observed KDP parameters are quite noisy. Furthermore the observed rain rates are moderate, where KDP is less significant than in heavy rain.

  16. 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.

  17. 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.

  18. The potential for hail and intense rainfall enhancement over urban areas: improving urban extreme weather risk assessment

    NASA Astrophysics Data System (ADS)

    Ntelekos, A. A.; Smith, J. A.; Krajewski, W. F.; Foote, M.

    2009-04-01

    Urban communities and their infrastructure are particularly vulnerable to the impacts of organized thunderstorm systems. Current models of urban extreme weather risk do not fully represent the complexity of the hydrometeorological processes involved, particularly in relation to intense convective precipitation and severe weather. Hail is a severe thunderstorm hazard that can be extremely damaging to property (especially automobiles, buildings and agriculture) over and in proximity to urban environments. This study identifies some of the mechanisms that future generations of catastrophe models should consider incorporating in their representation of hydrometeorlogical hazards in urban areas. In addition, such information could help to inform planning policy and improve urban resilience to extreme events. Evidence is provided that urban environments, through the existence of high-rise buildings and densely build-up areas, but also through air-pollution (aerosols) can potentially lead to an enhancement of both flooding and hail. Conclusions are drawn from two separate studies over the heavily urbanized corridor of the northeastern United States but could be expanded to apply to other urban areas. Observational and modelling (Weather Research and Forecasting - WRF) analyses of an extreme thunderstorm over the Baltimore, Maryland metropolitan area on 7 July 2004 provided evidence that the urban canopy redistributed heavy rainfall and convergence centres in the vicinity of the urban environment. Modelling analyses suggest that convective rainfall around the urban core was increased by about 30% due to the heterogeneities of land surface processes associated with the city of Baltimore. Chesapeake Bay also played an important role in rainfall distribution by acting as a divergence zone for northerly winds. Cloud-to-ground lightning analyses show that the city of Baltimore and the Chesapeake Bay combined played a role in the distribution of lightning in the periphery of the urban core. Detailed modelling analyses (WRF-Chem) of a series of convective storms over the New York City metropolitan area, suggest that under certain meteorological conditions, increased concentrations of aerosols can lead to better organization of convection, higher vertical velocities and significantly increased convective rainfall accumulations. Higher vertical velocities were more widespread and reached deeper atmospheric levels when meteorological conditions were favourable, under increased aerosol concentrations. Areas that are downstream of sources of aerosols (i.e. New York City) are more prone to experience convective enhancement.

  19. 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.

  20. 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

  1. 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...

  2. 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...

  3. 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.

  4. 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.

  5. 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.

  6. NEXRAD Single and Dual Polarization Radar-Rainfall Product Comparison for the NASA Iowa Flood Studies (IFloodS)

    NASA Astrophysics Data System (ADS)

    Seo, B.; Dolan, B.; Krajewski, W. F.; Rutledge, S. A.; Petersen, W. A.

    2013-12-01

    During the months of April to June 2013, NASA conducted a field experiment called Iowa Flood Studies (IFloodS) as part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission in the central and northeastern Iowa in the United States. The purpose of IFloodS is to enhance the understanding of flood-related precipitation processes in events worldwide. While there are multiple rainfall data sets (satellite, radar, and ground reference data products) available as legacy from IFloodS, the authors focus on the comparison of the NEXRAD single and dual polarization precipitation products to evaluate potential benefits of using dual polarization data for flood-related precipitation events. The Hydro-NEXRAD and CSU (Colorado State University)-HIDRO blended precipitation processing algorithms were used to generate single and dual polarization products, respectively. Data from four NEXRAD radars (Des Moines, IA; Davenport, IA; Minneapolis, MN; and La Crosse, WI) were combined to cover the study area. Uncertainties of both products using dense networks of ground reference (e.g., rain gauge and disdrometer) are characterized. Major differences and similarities based on the observed precipitation cases are also discussed.

  7. 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.

  8. 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.

  9. 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.

  10. 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'…

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Potential use of radar QPE for hydrological design

    NASA Astrophysics Data System (ADS)

    Marra, Francesco; Morin, Efrat

    2014-05-01

    Intensity-duration-frequency (IDF) curves are commonly used for flood management design, and are identified from rainfall records analyzing maximum intensity values for a set of given durations. This approach applies to raingauge measurements even if usual design applications would prefer catchment scale curves. Weather radar provides distributed rainfall estimates with high spatial and temporal resolutions; in this way it is able to exploit the dynamics and variability of extreme rainfall events over wide areas. Two main objections usually restrain this approach: the length of radar data records and the reliability of radar quantitative precipitation estimations (QPE). This work aims to explore the feasibility of using radar QPE for the identification of IDF curves by means of a long length radar data archive and a combined physical- and quantitative- adjustment of radar rainfall estimates. Two C-Band weather radars are located in the eastern Mediterranean area (Tel Aviv, Israel) and are operational since 1990 and 1997 respectively, providing relatively long-term records. Radar measurements are elaborated using physically-based correction algorithms and are then adjusted by removing the mean field bias with respect to ground observations. Accuracy of radar QPE is assessed by comparison with raingauge measurements using a bootstrap technique. IDF curves are calculated for a set of reference raingauges using different sources of rainfall information: i) raingauge data record ("true" IDF), ii) data record of the closest raingauge and iii) radar QPE obtained excluding the examined raingauge from the adjustment procedure. Accuracy of radar-based IDF compared to close by-raingauge IDF is assessed. Results of this on-going study will be presented leading to conclusions on the potential use of radar QPE for IDF estimation.

  20. Predicting road hazards caused by rain, freezing rain and wet surfaces and the role of weather radar

    NASA Astrophysics Data System (ADS)

    Symons, Leslie; Perry, Allen

    1997-03-01

    Freezing rain in the winter of 1995/96 has drawn attention to the severity of black-ice problems on British roads, additional to the normal increased hazards presented to drivers by any form of precipitation. Disruption to traffic was considerable on several days. Weather radar provides improved nowcasting, for both winter and summer conditions, where available real time directly to highway engineers, but this is not yet generally the case in England and Wales. New developments from the Meteorological Office offer improved possibilities at reasonable costs.

  1. Simultaneous ocean cross-section and rainfall measurements from space with a nadir-pointing radar

    NASA Technical Reports Server (NTRS)

    Meneghini, R.; Atlas, D.

    1984-01-01

    A method to determine simultaneously the rainfall rate and the normalized backscattering cross section of the surface was evaluated. The method is based on the mirror reflected power, p sub m which corresponds to the portion of the incident power scattered from the surface to the precipitation, intercepted by the precipitation, and again returned to the surface where it is scattered a final time back to the antenna. Two approximations are obtained for P sub m depending on whether the field of view at the surface is either much greater or much less than the height of the reflection layer. Since the dependence of P sub m on the backscattering cross section of the surface differs in the two cases, two algorithms are given by which the path averaged rain rate and normalized cross section are deduced. The detectability of P sub m, the relative strength of other contributions to the return power arriving simultaneous with P sub m, and the validity of the approximations used in deriving P sub m are discussed.

  2. 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.

  3. 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.

  4. 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.

  5. Parameterizing road construction in route-based road weather models: can ground-penetrating radar provide any answers?

    NASA Astrophysics Data System (ADS)

    Hammond, D. S.; Chapman, L.; Thornes, J. E.

    2011-05-01

    A ground-penetrating radar (GPR) survey of a 32 km mixed urban and rural study route is undertaken to assess the usefulness of GPR as a tool for parameterizing road construction in a route-based road weather forecast model. It is shown that GPR can easily identify even the smallest of bridges along the route, which previous thermal mapping surveys have identified as thermal singularities with implications for winter road maintenance. Using individual GPR traces measured at each forecast point along the route, an inflexion point detection algorithm attempts to identify the depth of the uppermost subsurface layers at each forecast point for use in a road weather model instead of existing ordinal road-type classifications. This approach has the potential to allow high resolution modelling of road construction and bridge decks on a scale previously not possible within a road weather model, but initial results reveal that significant future research will be required to unlock the full potential that this technology can bring to the road weather industry.

  6. 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.

  7. Proposed adopted environmental assessment for the next generation weather radar facility at Brookhaven National Laboratory. [NEXRAD Facility

    SciTech Connect

    Not Available

    1992-06-01

    The US Department of Commerce (DOC) completed an environmental impact assessment review, under the National Environmental Policy Act (NEPA), on its decisions for the nationwide Next Generation Weather Radar (NEXRAD) program of 150 radar units and for the site specific assessments of impacts. The DOC published a Programmatic Enviornmental Impact Statement on NEXRAD in November 1984. It completed a site-specific Environmental Assessment (EA) on the proposed NEXRAD facility at DOE's Brookhaven National Laboratory (BNL) in November 1991 and issued a Finding of No Significant Impact (FONSI) on March 12, 1992. The DOC EA is included. The Department of Energy (DOE) proposes to adopt, in its entirety, the November 1991 site-specific EA prepared by the DOC for construction and operation of the NEXRAD facility and a National Weather Service (NWS) office building at BNL. The DOE's decision is whether or not to lease a tract of land on DOE property to the DOC for use by the NWS. The DOE has performed an an in-depth review of the DOC EA to verify its accuracy and completeness, and to ensure that it encompasses the environmental issues at BNL relevant to the DOE proposed action for lease of land to the DOC. The DOE, therefore, proposes to adopt the DOC EA in its entirety by preparation of this brief addendum to assess the impacts.

  8. 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.

  9. 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.

  10. Weather.

    ERIC Educational Resources Information Center

    Web Feet K-8, 2000

    2000-01-01

    This subject guide to weather resources includes Web sites, CD-ROMs and software, videos, books, audios, magazines, and professional resources. Related disciplines are indicated, age levels are specified, and a student activity is included. (LRW)

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. The use of weather radars to estimate hail damage to automobiles: an exploratory study in Switzerland

    NASA Astrophysics Data System (ADS)

    Hohl, Roman; Schiesser, Hans-Heinrich; Knepper, Ingeborg

    As the first of its kind, this study presents damage functions between two damage variables of hail-damaged automobiles and radar-derived hail kinetic energy for a total of 12 severe hailstorms that have occurred over the Swiss Mittelland (1992-1998). Hail kinetic energy is calculated from C-band Doppler radar CAPPIs at low storm level (1.5 km MSL) and is integrated per radar element ( EKINPIX) for entire hail cells. Hail damage claim data were available per Swiss community on a daily basis and transformed (Delaunay triangulation) along with EKINPIX to a regular 3×3 km grid, thereafter allowing cross-correlation between the variables. The results show nonlinear relationships between EKINPIX and both loss ratios and mean damages per hail-damaged car, differing between high hail season storms (15 June-15 August) and storms that occurred during the low season (before and after). A weighted logistic function provides correlation coefficients between EKINPIX and loss ratios of 0.71 (0.79) for high (low) season storms and 0.76 (0.40) for mean damages of high (low) season hailstorms. Maximally possible loss ratios reach 60% (40%) in high (low) season storms with maximum mean damages of CHF 6000 (CHF 3000) and average values around CHF 3100 (CHF 2100). Seasonal differences in hailfall intensities are discussed in terms of atmospheric conditions favoring convective activity and the likelihood of higher numbers of large hailstones (>20 mm in diameter) that induce more severe damage to cars during the high storm season. The results suggest that radar-derived hail kinetic energy could be used by insurance companies in the future to (1) assess hail damage to cars immediately after a storm has passed over a radar observation area and (2) to estimate potential maximal hail losses to car portfolios for parts of central Europe.

  17. 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.

  18. Radar data bias correction implementing quantile mapping and investigation of its influence in a hydrological model

    NASA Astrophysics Data System (ADS)

    Rabiei, Ehsan; Wallner, Markus; Haberlandt, Uwe

    2014-05-01

    Weather radar is an important source of data for estimating rainfall rate with relatively high temporal and spatial resolution covering large areas. Although weather radar provides fine temporal and spatial resolution data, it is subject to different sources of error. Beside casual problems associated with radar, e.g. clutter and attenuation, weather radar either underestimates or overestimates the rainfall amount. Additionally, time steps with strangely high values result in destroying the structure of time series derived from radar data. In order to estimate areal precipitation for hydrological analyses, radar data could be merged with rain gauge network data. The merging product quality is strongly dependent on radar data quality. The main purpose of this study is to illustrate a method for improving radar data quality and to investigate the influence of radar data quality on merging products by means of cross validation. Quantile mapping on the two sources of data, the radar and rain gauge network, is implemented in this study to improve the radar data quality. After correcting the radar data, considering rain gauge data as the truth, the data is implemented into a hydrological model, HBV-IWW, to investigate the influence of the different input sources regarding model performance. It has been observed that implementing quantile mapping improves radar data quality significantly. On the other hand, using radar data after correction not only improves interpolation performances but also reveals other possible applications like disaggregation of daily rainfall data into finer temporal resolutions. Beside radar data quality, there are other factors influencing the model performance like network density and the applied interpolation technique. The study area is a mesoscale catchment located in Lower Saxony, northern Germany.

  19. 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.

  20. 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.

  1. 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.

  2. Interpretation of Doppler Weather Radar Displays of Midlatitude Mesoscale Convective Systems.

    NASA Astrophysics Data System (ADS)

    Houze, Robert A., Jr.; Biggerstaff, M. I.; Rutledge, S. A.; Smull, B. F.

    1989-06-01

    The utility of color displays of Doppler-radar data in revealing real-time kinematic information has been demonstrated in past studies, especially for extratropical cyclones and severe thunderstorms. Such displays can also indicate aspects of the circulation within a certain type of mesoscale convective system-the squall line with trailing "stratiform" rain. Displays from a single Doppler radar collected in two squall-line storms observed during the Oklahoma-Kansas PRE-STORM project conducted in May and June 1985 reveal mesoscale-flow patterns in the stratiform rain region of the squall line, such as front-to-rear storm-relative flow at upper levels, a subsiding storm-relative rear inflow at middle and low levels, and low-level divergent flow associated with strong mesoscale subsidence. "Dual-Doppler" analysis further illustrates these mesoscale-flow features and, in addition, shows the structure of the convective region within the squall line and a mesoscale vortex in the "stratiform" region trailing the line. A refined conceptual model of this type of mesoscale convective system is presented based on previous studies and observations reported here.Recognition of "single-Doppler-radar" patterns of the type described in this paper, together with awareness of the conceptual model, should aid in the identification and interpretation of this type of mesoscale system at future NEXRAD sites. The dual-Doppler results presented here further indicate the utility of multiple-Doppler observations of mesoscale convective systems in the STORM program.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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 Rhône 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 km². 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.

  8. 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.

  9. 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.

  10. Intercomparison Experiments with an X-band Polarimetric Radar

    NASA Astrophysics Data System (ADS)

    Domaszczynski, P.; Niemeier, J. J.; Kruger, A.; Ceynar, D.; Krajewski, W. F.

    2009-12-01

    Polarimetric, X-band radars are capable of more precise measurements of differential phase shift (Kdp) and greater sensitivity in reflectivity measurements (Zh, Zdr) when compared to bigger, more expensive S- and C-band weather radars. Those advantages can lead to better characterization of spatial and temporal rainfall structure through precise estimation of drop size distribution (DSD). This is possible only after radar data is corrected for attenuation which can be significant at X-band frequencies. In this study we present a set of experiments centered around The University of Iowa’s, mobile, polarimetric X-band radar. We designed the experiments to better understand the performance of the radar in estimating rainfall rates, accumulations, vertical profiles of DSD, wind velocity and wind direction. Our experimental setup incorporates instruments that include tipping bucket raingauges, a-newly-developed microwave raingauge, an experimental microwave disdrometer, a Vaisala Weather Transmitter (anemometer, barometric pressure, relative humidity, and rainfall), and a Thies optical disdrometer. All instruments are operated in immediate proximity to the radar, with the radar operated at vertical or close-to-vertical antenna elevations. We present and discuss data collected during the experiment.

  11. Tropical Rainfall Measuring Mission (TRMM) project. III - Japan-U.S. collaborative rain observation experiment using an airborne rain radar

    NASA Technical Reports Server (NTRS)

    Meneghini, Robert; Atlas, David; Nakamura, Kenji; Kozu, Toshiaki

    1990-01-01

    A collaborative rain-observation experiment using an airborne rain radar was conducted between Communications Research Laboratory (CRL) and Goddard Space Flight Center (GSFC)/NASA. CRL provided an airborne rain-radar/radiometer system and GSFC/NASA provided a NASA P3-A aircraft. Airborne or spaceborne rain-radar echoes have large sea or land-surface echoes. These surface echoes yield rain-estimation algorithms using rain attenuation. The experiment demonstrated the potential of the rain-estimation techniques using rain attenuation.

  12. The Joint Polarization Experiment: Polarimetric Rainfall Measurements and Hydrometeor Classification.

    NASA Astrophysics Data System (ADS)

    Ryzhkov, Alexander V.; Schuur, Terry J.; Burgess, Donald W.; Heinselman, Pamela L.; Giangrande, Scott E.; Zrnic, Dusan S.

    2005-06-01

    As part of the evolution and future enhancement of the Next Generation Weather Radars (NEXRAD), the National Severe Storms Laboratory recently upgraded the KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) to include a polarimetric capability. The proof of concept was tested in central Oklahoma during a 1-yr demonstration project referred to as the Joint Polarization Experiment (JPOLE). This paper presents an overview of polarimetric algorithms for rainfall estimation and hydrometeor classification and their performance during JPOLE. The quality of rainfall measurements is validated on a large dataset from the Oklahoma Mesonet and Agricultural Research Service Micronet rain gauge networks. The comparison demonstrates that polarimetric rainfall estimates are often dramatically superior to those provided by conventional rainfall algorithms. Using a synthetic R(Z, KDP, ZDR) polarimetric rainfall relation, rms errors are reduced by a factor of 1.7 for point measurements and 3.7 for areal estimates [when compared to results from a conventional R(Z) relation]. Radar data quality improvement, hail identification, rain/snow discrimination, and polarimetric tornado detection are also illustrated for selected events.


  13. 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.

  14. High-resolution summer rainfall prediction in the JHWC real-time WRF system

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Kyou; Eom, Dae-Yong; Kim, Joo-Wan; Lee, Jae-Bok

    2010-08-01

    The WRF-based real-time forecast system (http://jhwc.snu.ac.kr/weather) of the Joint Center for High-impact Weather and Climate Research (JHWC) has been in operation since November 2006; this system has three nested model domains using GFS (Global Forecast System) data for its initial and boundary conditions. In this study, we evaluate the improvement in daily and hourly weather prediction, particularly the prediction of summer rainfall over the Korean Peninsula, in the JHWC WRF (Weather Research and Forecasting) model system by 3DVAR (three-Dimensional Variational) data assimilation using the data obtained from KEOP (Korea Enhanced Observation Program). KEOP was conducted during the period June 15 to July 15, 2007, and the data obtained included GTS (Global Telecommunication System) upper-air sounding, AWS (Automatic Weather System), wind profiler, and radar observation data. Rainfall prediction and its characteristics should be verified by using the precipitation observation and the difference field of each experiment. High-resolution (3 km in domain 3) summer rainfall prediction over the Korean peninsula is substantially influenced by improved synoptic-scale prediction in domains 1 (27 km) and 2 (9 km), in particular by data assimilation using the sounding and wind profiler data. The rainfall prediction in domain 3 was further improved by radar and AWS data assimilation in domain 3. The equitable threat score and bias score of the rainfall predicted in domain 3 indicated improvement for the threshold values of 0.1, 1, and 2.5 mm with data assimilation. For cases of occurrence of heavy rainfall (7 days), the equitable threat score and bias score improved considerably at all threshold values as compared to the entire period of KEOP. Radar and AWS data assimilation improved the temporal and spatial distributions of diurnal rainfall over southern Korea, and AWS data assimilation increased the predicted rainfall amount by approximately 0.3 mm 3hr-1.

  15. Spaced-antenna wind estimation using an X-band active phased-array weather radar

    NASA Astrophysics Data System (ADS)

    Venkatesh, Vijay

    Over the past few decades, several single radar methods have been developed to probe the kinematic structure of storms. All these methods trade angular-resolution to retrieve the wind-field. To date, the spaced-antenna method has been employed for profiling the ionosphere and the precipitation free lower atmosphere. This work focuses on applying the spaced-antenna method on an X-band active phased-array radar for high resolution horizontal wind-field retrieval from precipitation echoes. The ability to segment the array face into multiple displaced apertures allows for flexible spaced-antenna implementations. The methodology employed herein comprises of Monte-Carlo simulations to optimize the spaced-antenna system design and analysis of real data collected with the designed phased-array system. The contribution that underpins this dissertation is the demonstration of qualitative agreement between spaced-antenna and Doppler beam swinging retrievals based on real data. First, simulations of backscattered electric fields at the antenna array elements are validated using theoretical expressions. Based on the simulations, the degrees of freedom in the spaced-antenna system design are optimized for retrieval of mean baseline wind. We show that the designed X-band spaced-antenna system has lower retrieval uncertainty than the existing S-band spaced-antenna implementation on the NWRT. This is because of the flexibility to synthesize small overlapping apertures and the ability to obtain statistically independent samples at a faster rate at X-band. We then demonstrate a technique to make relative phase-center displacement measurements based on simulations and real data from the phased-array spaced-antenna system. This simple method uses statistics of precipitation echoes and apriori beamwidth measurements to make field repeatable phase-center displacement measurements. Finally, we test the hypothesis that wind-field curvature effects are common to both the spaced-antenna and Doppler beam swinging methods. Based on a close-range winter storm data set, we find that the spaced-antenna and fine-resolution Doppler beam swinging retrievals are in qualitative agreement. The correlation between the spaced-antenna and fine-resolution Doppler beam swinging retrievals was 0.57. The lowered correlation coefficient was, in part, due to the high standard deviation of the DBS retrievals. At high wind-speeds, the spaced-antenna retrievals significantly departed from variational retrievals of mean baseline wind.

  16. 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%).

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Ground Penetrating Radar as a Means of Studying Palaeofault Scarps in a Deeply Weathered Terrain, Southwestern Western Australia

    NASA Astrophysics Data System (ADS)

    Dentith, M. C.; O'Neill, A.; Clark, D.

    2009-12-01

    The southwest seismic zone is a region of concentrated intra-plate seismicity in the southwest of Western Australia. The regional geology consists of Archean granitoids covered by a thick, electrically conductive, mantle of in situ weathered material and transported cover. Numerous palaeofault scarps have been recognised in the region, primarily based on remote sensing data. These scarps occur in an area more extensive than the historic region of seismic activity, implying that large seismic events can occur outside the current seismic zone, which has important implications for the estimation of seismic hazard. Ground penetrating radar (GPR) has been used to study Recent faulting in various parts of the world, and been shown to be capable of imaging features associated with the fault, e.g. colluvial wedges, disrupted and displaced strata. However, the majority of studies are of normal and/or strike-slip faults and there are no studies demonstrating the method works in electrically conductive, deeply weathered terrains. GPR data have been collected in Western Australia across confirmed two palaeofault scarps (Hyden and Dumbelyung) and also the scarp created by the 1968 Meckering earthquake. In each case there is a nearby trench to allow GPR responses to be related to known geology. At Meckering and Hyden, where the near-surface material contains moderate amounts of clay and the groundwater is fresh, it has proved possible to collect high quality data that images colluvium and also disrupted bedrock features which allow faults to be inferred. At Dumbelyung, where the near surface is more conductive due to clay-rich alluvial deposits and saline groundwater, results were less good and no sub-surface features were confidently identified, although the general geometry of the stratigraphy was imaged. Our results demonstrate that GPR surveys can be a valuable tool for studying palaeofaults in deeply weathered terrains, although this is subject to the local ground conditions. Even in what is considered a hostile environment for the method, GPR data can confirm whether a topographic feature is of seismic origin, and image features in sufficient detail to enable siting of trenches for palaeoseismic studies.

  2. Ground penetrating radar as a means of studying palaeofault scarps in a deeply weathered terrain, southwestern Western Australia

    NASA Astrophysics Data System (ADS)

    Dentith, Mike; O'Neill, Adam; Clark, Dan

    2010-10-01

    The southwest seismic zone is a region of concentrated intra-plate seismicity in the southwest of Western Australia. The regional geology consists of Archean granitoids covered by a thick, electrically conductive, mantle of in situ weathered material and transported cover. Numerous palaeofault scarps have been recognised in the region, primarily based on remote sensing data. These scarps are primarily caused by reverse faulting, which is consistent with the results of focal mechanism studies of the earthquakes in the area. The scarps occur across an area more extensive than the historic region of seismic activity, implying that large seismic events can occur outside the current seismic zone, which has obvious implications for the estimation of seismic hazard. Ground penetrating radar (GPR) has been used to study Quaternary faulting in various parts of the world, and has been shown to be capable of imaging features associated with such faults, e.g. colluvial wedges, disrupted and displaced strata. However, the majority of studies are of normal and/or strike-slip faults and there are no studies demonstrating the method is useful in electrically conductive, deeply weathered terrains. GPR data have been collected across known palaeofault scarps at Hyden and Dumbleyung, and also the scarp created by the 1968 Meckering earthquake, all located in southwestern Western Australia. In each case there is a nearby trench to allow GPR responses to be related to known geology. At Meckering and Hyden, where the near-surface material contains moderate amounts of clay and the groundwater is fresh, it has proved possible to collect high quality data that images colluvium and also disrupted bedrock features which allow faults to be inferred. At Dumbleyung, where the near surface is more conductive due to clay-rich alluvial deposits and saline groundwater, the GPR data were of poorer quality and no sub-surface features were confidently identified, although the general geometry of the stratigraphy was imaged. This may also be the result of the scarp comprising a monoclinic fold rather than consisting of a hangingwall fault block above a fault that extends to the surface. Our results demonstrate that GPR surveys can be a valuable tool for studying palaeofaults in deeply weathered terrains, although this is subject to the local ground conditions. Even in what is considered a hostile environment for the method, GPR data can confirm whether a topographic feature is of seismic origin, and image features in sufficient detail to enable siting of trenches for palaeoseismic studies.

  3. Diurnal patterns of rainfall in a tropical Andean valley of southern Ecuador as seen by a vertically pointing K-band Doppler radar

    NASA Astrophysics Data System (ADS)

    Bendix, Jörg; Rollenbeck, Rütger; Reudenbach, Christoph

    2006-05-01

    The diurnal precipitation dynamics in an east-west-oriented valley that connects the Amazon lowlands and the inter-Andean basin of southern Ecuador (Rio San Francisco valley) is investigated by means of a K-band rain-radar profiler (located at the ECSF research station, latitude: 3° 58'S, longitude: 79° 4W) and additional remotely sensed data. A pre-dawn/dawn (5:30-6:30 LST) maximum of rainfall is found and a secondary peak is observed after noon (14:30-15:30 LST). Although the frequency distribution of rain rates reveals that a great portion of rainfall is of stratiform character, vertical profiles of rain rate and droplet concentration points to the important contribution of embedded convection and/or showers produced by local heating for the overall amount of rainfall. Specific differences in stratification and process dynamics could be found for both peak times. The pre-dawn maximum can be related to mesoscale instabilities over the Peruvian Amazon close to the south Ecuadorian border. Extended cold air drainage flow from the Andes and low-level confluence due to the concavity of the Andean chain in this area leads to convective instability in the nocturnal Amazonian boundary layer, which is extended to the study area by the predominant easterlies in the mid-troposphere. Rain clouds with at least embedded shallow convection can overflow the bordering ridges of the San Francisco valley providing rains of higher intensity at the ECSF research station. On the contrary, the afternoon convective precipitation can be caused by locally induced thermal convection at the bordering slopes (up-slope breeze system) where the ECSF station profits from precipitation off the edge of these local cells due to the narrow valley.

  4. Estimating Rainfall One Pixel at a Time: A Scientific Activity with Brazilian Students

    NASA Astrophysics Data System (ADS)

    Alves, M. A.; Martin, I. M.; Lyra, C. S.

    2009-12-01

    Studies of rainfall and precipitation using radars started almost at the same time as radars were developed for military applications in Second World War. Since then, the science behind radars used to monitor weather has evolved constantly. Radar images showing clouds, different types of precipitation, motion and evolution of weather systems are commonplace nowadays and are present in all forms of mass communication. Unfortunately, the layperson and even science students have limited knowledge of how weather radars work, how radar images are produced and what they do really mean. In order to increase the awareness about the use of radars in meteorology and interpretation of images, we started a program to teach science students on how to analyze radar images and to obtain simple estimates of rainfall using radar images alone. The data for the study was collected by a non-polarimetric Doppler radar operating on the C-Band The procedure is simple, radar images are selected, areas of interest (rain cells) are marked and then the color pixels in images are separated and counted according to their color and precipitation index. In this way, the evolution of the rain cell is followed and the amount of precipitation is calculated. As an additional activity, in a reverse analysis process, values of reflectivity are obtained from the estimates of precipitation and the size distribution of rain cloud droplets are calculated using parametric equations. This study was both rewarding and enriching for the students because they could participate in the actual process of collecting and analyzing the data, and the lessons learned and experience gained with this hands-on activity will certainly constitute a valuable asset.

  5. 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. A comparison between two probabilistic radar-based nowcasting methods

    NASA Astrophysics Data System (ADS)

    Buil, Alejandro; Berenguer, Marc; Sempere-Torres, Daniel

    2013-04-01

    Until now, some algorithms have been developed for very short-term precipitation forecasting based on radar data. Unlike deterministic methods, probabilistic nowcasting techniques aim at describing the uncertainty in the forecasts. This work presents a comparison of two probabilistic nowcasting techniques based on Lagrangian extrapolation of recent radar observations. Germann and Zawadzki (2004) described and evaluated four probabilistic techniques. We have chosen to compare the so-called Local Lagrangian technique [the one that demonstrated the best skill,among those of Germann and Zawadzki (2004)] with the ensemble nowcasting technique SBMcast (Berenguer et al., 2011). These two methods are conceptually different: while the Local Lagrangian techinque forecasts pdfs of point rainfall values calculated examining the spatial variability of the radar field, SBMcast generates a set of future rainfall scenarios (ensemble members) compatible with the observations keeping spatial and temporal structure of the rainfall field according to the String of Beads model. The comparison of these methods has been carried out in the vicinity of Barcelona, Catalunya (Spain) using the observations of the Catalan Weather Service radar network. References Berenguer, M., D. Sempere-Torres, and G. Pegram, 2011: SBMcast-An ensemble nowcasting technique to assess the uncertainty in rainfall forecasts by Lagrangian extrapolation.Journal of Hydrology, 404, 226-240. Germann, U. and I. Zawadzki, 2004: Scale dependence of the predictability of precipitation from the continental radar image. Part II: Probability forecasts. Journal of Applied Meteorology, 43, 74-89.

  12. Real-time flood forecasting with high-resolution NWP rainfall and dual data assimilation

    NASA Astrophysics Data System (ADS)

    Liu, Jia; Bray, Michaela; Han, Dawei

    2014-05-01

    Mesoscale Numerical Weather Prediction (NWP) models are nowadays gaining more and more attention in providing high-resolution rainfall forecasts for real-time flood forecasting. In this study, the newest generation NWP model, Weather Research & Forecasting (WRF) model, is integrated with the rainfall-runoff model in real-time to generate accurate flow forecasts at the catchment scale. The rainfall-runoff model is chosen as the Probability Distribution Model (PDM), which has widely been used for flood forecasting. Dual data assimilation is carried out for real-time updating of the flood forecasting system. The 3-Dimensional Variational (3DVar) data assimilation scheme is incorporated with WRF to assimilate meteorological observations and weather radar reflectivity data in order to improve the WRF rainfall forecasts; meanwhile real-time flow observations are assimilated by the Auto-Regressive Moving Average (ARMA) model to update the forecasted flow transformed by PDM. The Brue catchment located in Southwest England with a drainage area of 135.2 km2 is chosen to be the study area. A dense rain gauge network was set up during a project named HYREX (Hydrological radar experiment), which contains 49 rain gauges and a C-band weather radar, providing with sufficient hydrological and radar data for WRF model verification and data assimilation. Besides the radar reflectivity data, two types of NCAR archived data (SYNOP and SOUND, http://dss.ucar.edu) are also assimilated by 3DVar, which provide real-time surface and upper-level observations of pressure, temperature, humidity and wind from fixed and mobile stations. Four 24 hour storm events are selected from the HYREX project with different characteristics regarding storm formation and rainfall-runoff responses. Real-time flood forecasting is then carried out by the constructed forecasting system for the four storm events with a forecast lead time of 12 hours. The forecasting accuracy of the whole system is found to be largely improved by incorporating the WRF forecasted rainfall when the forecast lead time is beyond the catchment concentration time. The assimilation of real-time meteorological and radar data also show great advantage in improving the performance of the flood forecasting system. Key words: real-time flood forecasting; Weather Research & Forecasting (WRF) model; high-resolution rainfall forecasts; dual data assimilation.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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 ?S 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.

  18. Performance of rain reflectivity and differential reflectivity rainfall algorithms at X-band

    NASA Astrophysics Data System (ADS)

    Baldini, L.; Gorgucci, E.; Romaniello, V.

    2009-04-01

    X-band weather radar systems present several advantages mainly related to their low cost and small size. The main drawback of these systems is the attenuation suffered by the electromagnetic wave propagating through precipitation that reduces the reliability of rainfall estimates based on power measurements. Dual-polarization techniques provide solutions to mitigate the impact of attenuation and have renovated the interest on X-band radar systems. Different algorithms are available to estimate rainfall rate using the dual polarization radar measurements namely, reflectivity factor (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp). At X-band, attenuation affects any radar parameter based on backscatter power measurements such as Zh, while differential attenuation affects parameters based on differential power measurement such as Zdr. that must be corrected prior to use in quantitative applications such as rainfall estimation. However, correction procedures could introduce additional errors that impact on rain estimation. The rainfall estimation obtained with attenuation corrected measurements can be even worse that that obtained from uncorrected measurements. Consequently, attenuation correction procedure must be performed only when needed. When using the X-band rain algorithm based on Zh and Zdr, the biases due to attenuation and differential attenuation nearly cancel each other and result in a small bias in the rainfall rate estimation. This paper investigates this property of X-band dual-polarization measurements.

  19. 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).

  20. 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.

  1. 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.

  2. Observed and NWP simulated rainfall uncertainty cascading into rainfall-runoff and flood inundation impact models

    NASA Astrophysics Data System (ADS)

    Souvignet, M.; Freer, J. E.; de Almeida, G. A.; Coxon, G.; Neal, J. C.; Champion, A.; Cloke, H. L.; Bates, P. D.

    2013-12-01

    Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade is still poorly understood. Such a project requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and hydraulic flood wave propagation based on the runoff predictions. Accounting for uncertainty in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures as part of the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions which are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated. The study is performed in the Severn catchment over summer 2007, where a series of large rainfall events (over 100mm between the 20th and 21rst of July in certain sub-catchments) caused record floods in the study area. Differences in water level at benchmark stations are compared and the resulting prediction uncertainties are analysed for the different rainfall products. These results quantify how different cascading techniques and rainfall input uncertainty affects the resultant set of behavioural simulations. This allows us to compare the performance of different rainfall products for real forecasting situations.

  3. 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).

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Simulation of polarimetric radar variables in rain at S-, C- and X-band wavelengths

    NASA Astrophysics Data System (ADS)

    Teschl, F.; Randeu, W. L.; Schönhuber, M.; Teschl, R.

    2008-04-01

    Polarimetric radar variables of rainfall events, like differential reflectivity ZDR, or specific differential phase KDP, are better suited for estimating rain rate R than just the reflectivity factor for horizontally polarized waves, ZH. A variety of physical and empirical approaches exist to estimate the rain rate from polarimetric radar observables. The relationships vary over a wide range with the location and the weather conditions. In this study, the polarimetric radar variables were simulated for S-, C- and X-band wavelengths in order to establish radar rainfall estimators for the alpine region of the form R(KDP), R(ZH, ZDR), and R(KDP), ZDR. For the simulation drop size distributions of hundreds of 1-minute-rain episodes were obtained from 2D-Video-Distrometer measurements in the mountains of Styria, Austria. The sensitivity of the polarimetric variables to temperature is investigated, as well as the influence of different rain drop shape models - including recently published ones - on radar rainfall estimators. Finally it is shown how the polarimetric radar variables change with the elevation angle of the radar antenna.

  10. Probing the Architecture of the Weathering Zone in a Tropical System in the Rio Icacos Watershed (Puerto Rico) With Drilling and Ground Penetrating Radar (GPR)

    NASA Astrophysics Data System (ADS)

    Orlando, J.; Comas, X.; Mount, G. J.; Brantley, S. L.

    2012-12-01

    Weathering processes in rapidly eroding systems such as humid tropical environments are complex and not well understood. The interface between weathered material (regolith) and non-weathered material (bedrock) is particularly important in these systems as it influences water infiltration and groundwater flow paths and movement. Furthermore, the spatial distribution of this interface is highly heterogeneous and difficult to image with conventional techniques such as direct coring and drilling. In this work we present results from a preliminary geophysical study in the Luquillo Critical Zone Observatory (LCZO) located in the rain forest in the Luquillo Mountains of northeastern Puerto Rico. The Luquillo Mountains are composed of volcaniclastic rocks which have been uplifted and metamorphosed by the Tertiary Rio Blanco quartz diorite intrusion. The Rio Blanco quartz diorite weathers spheroidally, creating corestones of relatively unweathered material that are surrounded by weathered rinds. A number of boreholes were drilled near the top of the Rio Icacos watershed, where the corestones are thought to be in the primary stages of formation, to constrain the regolith/bedrock interface and to provide an understanding of the depth to which corestones form. The depth of the water table was also a target goal in the project. Drilling reveals that corestones are forming in place, separated by fractures, even to depths of 10s of meters below ground surface. One borehole was drilled to a depth of about 25 meters and intersected up to 7 bedrock blocks (inferred to be incipient corestones) and the water table was measured at about 15 meters. Ground Penetrating Radar surveys were conducted in the same location to determine if GPR images variable thicknesses of saprolite overlying corestones. GPR common offset measurements and common midpoint surveys with 50, 100, and 200 MHz antenna frequencies were combined with borehole drillings in order to constrain geophysical results. We will compare drilling observations to GPR data to understand: 1) the lateral extent of the regolith-bedrock interface; 2) distribution of rindlets or spheroidal fracturing around corestones; and 3) presence and extent of corestones. This work has implications for understanding the rate of weathering advance and changes in permeability across rapidly eroding watersheds.

  11. Study of a Winter Monsoon Front over the South China Sea by Multi-Sensor Satellite and Weather Radar Data, and a Numerical Model

    NASA Astrophysics Data System (ADS)

    Alpers, Werner; Wong, Wai Kin; Dagestad, Knut-Frode; Chan, Pak Wai

    2013-03-01

    An atmospheric frontal system over the South China Sea (SCS) arising from the replenishment of the northeast monsoon is investigated by using multi-sensor satellite data, weather radar data, and a numerical model. The replenishment or freshening of the northeast monsoon results from the merging of high pressure areas over the Chinese Continent. The near-sea surface wind field associated with this event was measured by the Advanced Scatterometer (ASCAT) onboard the European MetOp satellite and the Advanced Synthetic Aperture Radar (ASAR) onboard the European Envisat satellite. The high resolution ASAR image reveals that the frontal line separating this wind field from the synoptic-scale ambient wind field is as sharp as in the case of a cold air outbreak and contains embedded rain cells. Furthermore, it shows that this replenishment was associated with northeasterly winds with speeds of up to 13 ms-1 over the SCS at offshore distances larger than 60 km, but only with speeds of around 6 ms-1 near the coast. The comparison of the observational data with model results of the pre-operational version of the AIR (Atmospheric Integrated Rapid-cycle) forecast model of the Hong Kong Observatory shows that the AIR model can successfully simulate the time evolution of the frontal system and the wind field over the open ocean, but fails to simulate the wind field near the coast.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Characteristics of the 14 April 1999 Sydney hailstorm based on ground observations, weather radar, insurance data and emergency calls

    NASA Astrophysics Data System (ADS)

    Schuster, S. S.; Blong, R. J.; Leigh, R. J.; McAneney, K. J.

    2005-08-01

    Hailstorms occur frequently in metropolitan Sydney, in the eastern Australian State of New South Wales, which is especially vulnerable due to its building exposure and geographical location. Hailstorms challenge disaster response agencies and pose a great risk for insurance companies. This study focuses on the Sydney hailstorm of 14 April 1999 - Australia's most expensive insured natural disaster, with supporting information from two other storms. Comparisons are drawn between observed hailstone sizes, radar-derived reflectivity and damage data in the form of insurance claims and emergency calls. The "emergency response intensity" (defined by the number of emergency calls as a proportion of the total number of dwellings in a Census Collection District) is a useful new measure of the storm intensity or severity experienced. The area defined by a radar reflectivity ?55 dBZ appears to be a good approximation of the damage swath on ground. A preferred area for hail damage is located to the left side of storm paths and corresponds well with larger hailstone sizes. Merging hail cells appear to cause a substantially higher emergency response intensity, which also corresponds well to maximum hailstone sizes. A damage threshold could be identified for hailstone sizes around 2.5 cm (1 cm), based on the emergency response intensity (insurance claims). Emergency response intensity and claims costs both correlate positively with hailstone sizes. Higher claim costs also occurred in areas that experienced higher emergency response intensities.

  20. 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.

  1. A Mediterranean nocturnal heavy rainfall and tornadic event. Part II: Total lightning analysis

    NASA Astrophysics Data System (ADS)

    Pineda, Nicolau; Bech, Joan; Rigo, Tomeu; Montanyà, Joan

    2011-06-01

    On the night from 1st to 2nd of November 2008, a multi-cell storm coming from the Mediterranean produced severe weather in the coastal area of Catalonia (NE Spain): ground-level strong damaging wind gusts, a tornado - which caused F2 damage - and heavy rainfall. A general overview of the synoptic framework, damage observed and a radar analysis is given in the first part of the study. This second part is mostly centered on the detailed analysis of the total lightning behavior, its relationship with radar-derived storm parameters, and total lightning correlation with hazardous weather. The purpose is to bring more evidence about the outstanding role of total lightning in severe weather surveillance tasks. The analysis of the storm cells life cycle has showed similar trends between the total lighting flash rates and radar-derived parameters like the area of reflectivity above 30 dBZ at 7-km. Regarding lightning trends, a lightning "jump" pattern - an abrupt increase of the total lightning rate in a short period of time - has been related to severe weather. On the contrary, cloud-to-ground lightning data did not show any pattern related to severe weather. In comparison to other parameters, like the IC:CG ratio, the lightning "jump" pattern seems more robust to forecast in a short-term basis the possible occurrence of severe weather.

  2. 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.

  3. A comparison of NEXRAD WSR-88D radar estimates of rain accumulation with gauge measurements for high- and low-reflectivity horizontal gradient precipitation events.

    SciTech Connect

    Klazura, G. E.; Thomale, J. M.; Kelly, D. S.; Jendrowski, P.; Environmental Research; Univ. of Oklahoma; National Weather Service

    1999-11-01

    Radar-estimated rainfall amounts from the NEXRAD Weather Surveillance Radar precipitation accumulation algorithm were compared with measurements from numerous rain gauges (1639 radar versus gauge comparisons). Storm total rain accumulations from 43 rain events from 10 radar sites were analyzed. These rain events were stratified into two precipitation types: (1) high-reflectivity horizontal gradient storms and (2) low-reflectivity horizontal gradient events. Overall, the radar slightly overestimated rainfall accumulations for high-reflectivity gradient cases and significantly underestimated accumulations for low-reflectivity gradient cases. Varying degrees of range effects were observed for these two types of precipitation. For high-reflectivity gradient cases, the radar underestimated rainfall at the nearest ranges, overestimated at the middle ranges, and had fairly close agreements at the farthest ranges. A much stronger range bias was evident for low-reflectivity gradient cases. The radar underestimated rainfall by at least a factor of 2 in the nearest and farthest ranges, and to a somewhat lesser extent at midranges.

  4. Advancing Uses of Satellite Rainfall for Flood Modeling in Mountainous Basins

    NASA Astrophysics Data System (ADS)

    Anagnostou, E. N.; Nikolopoulos, E.; Bartsotas, N. S.; Solomos, S.; Kallos, G. B.

    2013-12-01

    Effective flood warning procedures are usually hampered by observational limitations at spatio-temporal scales associated with flash floods. Satellite rainfall remote sensing over mountainous regions that exhibit the most severe observational limitations offer a potentially viable solution to the observational coverage problem. However, satellite estimates of flood-triggering heavy rainfall events are associated with significant systematic errors associated with local orography that non-linearly propagate in hydrologic modeling. In this study we investigate the use of three quasi-global and near-real-time high-resolution satellite-rainfall products (3B42, PERSIANN, CMORPH) for simulating major flash flood events on medium size mountainous basins (600-1500 km2) in Western Mediterranean (South France and Italian Alps). Comparison of satellite rainfall with rainfall derived from gauge-calibrated weather radar estimates showed that systematic error in satellite rainfall was severely magnified when transformed to error in runoff (especially under dry initial soil conditions). Simulation hydrographs became meaningful after adjusting the satellite rainfall for underestimation due to retrieval bias and resolution effects determined based on high-resolution cloud-resolving storm simulations. Results of this study, based on some of the most significant heavy precipitation events that occurred in the last decade in Western Med mountainous region, highlight the use of high-resolution NWP analysis for determining local error adjustments to the satellite-rainfall products that allow a more appropriate use in flash-flood modeling.

  5. 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 Precipitation—Highly 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 27°N, 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.

  6. Cascading rainfall uncertainty into flood inundation impact models

    NASA Astrophysics Data System (ADS)

    Souvignet, Maxime; Freer, Jim E.; de Almeida, Gustavo A. M.; Coxon, Gemma; Neal, Jeffrey C.; Champion, Adrian J.; Cloke, Hannah L.; Bates, Paul D.

    2014-05-01

    Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade, and how best to approach this, is still poorly understood. This requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and finally the hydraulic flood wave propagation based on the runoff predictions. Improving the characterisation of uncertainty, and what is important to include, in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures using the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions that are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated. The study is performed in the Severn catchment over summer 2007, where a series of large rainfall events (over 100mm between the 20th and 21rst of July in certain sub-catchments) caused record floods in the study area. Differences in water level at benchmark stations are compared and the resulting prediction uncertainties are analysed for the different rainfall products. These results quantify how different cascading techniques and rainfall input uncertainty affects the resultant set of behavioural simulations. This allows us to compare the performance of different rainfall products used for real forecasting situations.

  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. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  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. Automatic morphing using image registration: Application to continuous tracking of radar reflectivity and rain fields

    NASA Astrophysics Data System (ADS)

    Vongsaard, Jearanai

    Rainfall is one of the most important natural phenomenon that influences human life. Accurate rainfall estimation and prediction are crucial for flood forecasting, flood control, climate diagnostics, and water resource management. Rain data may be collected from numerous sources. Conventional rain gauge networks or meteorological radars provide continuous coverage in time. Satellite observations provide snap-shots of precipitation fields at poor temporal resolution. While a number of spaceborne platforms have been deployed for rain observation, the development of continuous space/time rainfall remains a major challenge. This dissertation seeks alternative techniques to automatically generate continuous data streams of rainfall data from sparse or intermittent observations. In order to avoid human intervention in the process, an automatic procedure is needed for real-time operations. For this purpose, Automatic Morphing Using Image Registration (AMIR) model is developed by integrating automatic image registration and image morphing algorithm. The new AMIR technique uses automatic image registration as the basis for finding control points for the morphing process. In the study of data assimilation for weather forecasting, there is a need to generate continuous streams of rainfall data to alleviate the so-called "spin up" problem, or the inability to provide short-term forecasts [Road90]. The proposed algorithm has been tested using remote sensing images from Next Generation Weather Radars (NEXRAD) and Tropical Rainfall Measuring Mission (TRMM). Three cases of rainfall data have been used. These include the passage of a storm in Florida, hurricane Floyd, and scattered rain in the southwestern of the United States for the same period using NEXRAD radar data as surrogate for spaceborne observations. These cases have drastically different spatial and temporal characteristics and hence provide tests on the applicability of the AMIR method. Comparative experimental results have shown that AMIR advance the current state of the art as it is comparable to manual morphing and outperforms automatic morphing without control points proposed in literature.

  15. 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.

  16. 'Down-to-Earth' modelling of equivalent surface precipitation using multisource data and radar

    NASA Astrophysics Data System (ADS)

    Michelson, D. B.; Jones, C. G.; Landelius, T.; Collier, C. G.; Haase, G.; Heen, M.

    2005-04-01

    The estimation of surface rainfall from reflectivity data derived from weather radar has been much studied over many years. It is now clear that central to this problem is the adjustment of these data for the impacts of vertical variations in the reflectivity. In this paper a new procedure (known as Down-to-Earth, DTE) is proposed and tested for combining radar measurements aloft with information from a numerical weather-prediction (NWP) model and an analysis system. The procedure involves the exploitation of moist cloud physics in an attempt to account for physical processes impacting on precipitation during its descent from the height of radar echo measurements to the surface. The application of DTE leads to increased underestimation in the radar measurements compared to precipitation gauge observations at short and intermediate radar ranges (0-120 km), but is successful at reducing the bias at further ranges. However the application of DTE does not lead to significant decreases in the random error of the surface rain rate estimate. No improvement is made when attempting to account for the precipitation phase measured by radar. It is concluded that further work on radar data quality control, along with improvements to the NWP model, are essential to improve upon results using such a physically based procedure.

  17. 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.

  18. Stratiform and Convective Precipitation Observed by Multiple Radars during the DYNAMO/AMIE Experiment

    SciTech Connect

    Deng, Min; Kollias, Pavlos; Feng, Zhe; Zhang, Chidong; Long, Charles N.; Kalesse, Heike; Chandra, Arunchandra; Kumar, Vickal; Protat, Alain

    2014-11-01

    The motivation for this research is to develop a precipitation classification and rain rate estimation method using cloud radar-only measurements for Atmospheric Radiation Measurement (ARM) long-term cloud observation analysis, which are crucial and unique for studying cloud lifecycle and precipitation features under different weather and climate regimes. Based on simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two precipitation radars (NCAR S-PolKa and Texas A&M University SMART-R), and surface precipitation during the DYNAMO/AMIE field campaign, a new cloud radar-only based precipitation classification and rain rate estimation method has been developed and evaluated. The resulting precipitation classification is equivalent to those collocated SMART-R and S-PolKa observations. Both cloud and precipitation radars detected about 5% precipitation occurrence during this period. The convective (stratiform) precipitation fraction is about 18% (82%). The 2-day collocated disdrometer observations show an increased number concentration of large raindrops in convective rain compared to dominant concentration of small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also show two distinct structures for convective and stratiform rain. These indicate that the method produces physically consistent results for two types of rain. The cloud radar-only rainfall estimation is developed based on the gradient of accumulative radar reflectivity below 1 km, near-surface Ze, and collocated surface rainfall (R) measurement. The parameterization is compared with the Z-R exponential relation. The relative difference between estimated and surface measured rainfall rate shows that the two-parameter relation can improve rainfall estimation.

  19. Verification and correction of cloud base and top height retrievals from Ka-band cloud radar in Boseong, Korea

    NASA Astrophysics Data System (ADS)

    Oh, Su-Bin; Kim, Yeon-Hee; Kim, Ki-Hoon; Cho, Chun-Ho; Lim, Eunha

    2016-01-01

    In this study, cloud base height (CBH) and cloud top height (CTH) observed by the Ka-band (33.44 GHz) cloud radar at the Boseong National Center for Intensive Observation of Severe Weather during fall 2013 (September-November) were verified and corrected. For comparative verification, CBH and CTH were obtained using a ceilometer (CL51) and the Communication, Ocean and Meteorological Satellite (COMS). During rainfall, the CBH and CTH observed by the cloud radar were lower than observed by the ceilometer and COMS because of signal attenuation due to raindrops, and this difference increased with rainfall intensity. During dry periods, however, the CBH and CTH observed by the cloud radar, ceilometer, and COMS were similar. Thin and low-density clouds were observed more effectively by the cloud radar compared with the ceilometer and COMS. In cases of rainfall or missing cloud radar data, the ceilometer and COMS data were proven effective in correcting or compensating the cloud radar data. These corrected cloud data were used to cl