Science.gov

Sample records for weather radar rainfall

  1. Weather Radar

    NASA Astrophysics Data System (ADS)

    Vivekanandan, Jothiram

    2004-10-01

    Weather radar is an indispensable component for remote sensing of the atmosphere, and the data and products derived from weather radar are routinely used in climate and weather-related studies to examine trends, structure, and evolution. The need for weather remote sensing is driven by the necessity to understand and explain a specific atmospheric science phenomenon. The importance of remote sensing is especially evident in high-profile observational programs, such as the WSR-88D (Weather Surveillance Radar) network, TRMM (Tropical Rainfall Measuring Mission), and ARM (Atmospheric Radiation Measurement). A suite of ground-based and airborne radar instruments is maintained and deployed for observing wind, clouds, and precipitation. Weather radar observation has become an integral component of weather forecasting and hydrology and climate studies. The inclusion of weather radar observations in numerical weather modeling has enhanced severe storm forecasting, aviation weather, hurricane intensity and movement, and the global water cycle.

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

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  5. 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

  6. Gridded radar rainfall product for comparison with model rainfall

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  7. Dual-polarization radar rainfall estimation

    NASA Astrophysics Data System (ADS)

    Cifelli, Robert; Chandrasekar, V.

    Dual-polarization radar is a critical tool for weather research applications, including rainfall estimation, and is at the verge of being a key instrument for operational meteorologists. This new radar system is being integrated into radar networks around the world, including the planned upgrade of the U.S. National Weather Service Weather Surveillance Radar, 1988 Doppler radars. Dual polarization offers several advantages compared to single-polarization radar systems, including additional information about the size, shape, and orientation of hydrometeors. This information can be used to more accurately retrieve characteristics of the drop size distribution, identify types of hydrometeors, correct for signal loss (attenuation) in heavy precipitation, and more easily identify spurious echo scatterers. In addition to traditional backscatter measurements, differential propagation phase characteristics allow for rainfall estimation that is immune to absolute calibration of the radar system, attenuation effects, as well as partial beam blocking. By combining different radar measurements, rainfall retrieval algorithms have developed that minimize the error characteristics of the different rainfall estimators, while at the same time taking advantage of the data quality enhancements. Although dual-polarization techniques have been applied to S band and C band radar systems for several decades, polarization diversity at higher frequencies including X band are now widely available to the radar community. This chapter provides an overview of dual-polarization rainfall estimation applications that are typically utilized at X, C, and S bands. The concept of distinguishing basic and applied science issues and their impact on rainfall estimation is introduced. Various dual-polarization radar rainfall techniques are discussed, emphasizing the strengths and weaknesses of various estimators at different frequencies.

  8. 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

  9. 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

  10. 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.

  11. Spaceborne weather radar

    NASA Technical Reports Server (NTRS)

    Meneghini, Robert; Kozu, Toshiaki

    1990-01-01

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

  12. 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

  13. 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.

  14. 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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  17. 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

  18. Hydrologic applications of weather radar

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  2. 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…

  3. 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

  4. Propagation of radar rainfall uncertainty in urban flood simulations

    NASA Astrophysics Data System (ADS)

    Liguori, Sara; Rico-Ramirez, Miguel

    2013-04-01

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

  5. 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...

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. Close-range radar rainfall estimation and error analysis

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

    Quantitative precipitation estimation (QPE) using ground-based weather radar is affected by many sources of error. The most important of these are (1) radar calibration, (2) ground clutter, (3) wet-radome attenuation, (4) rain-induced attenuation, (5) vertical variability in rain drop size distribution (DSD), (6) non-uniform beam filling and (7) variations in DSD. This study presents an attempt to separate and quantify these sources of error in flat terrain very close to the radar (1-2 km), where (4), (5) and (6) only play a minor role. Other important errors exist, like beam blockage, WLAN interferences and hail contamination and are briefly mentioned, but not considered in the analysis. A 3-day rainfall event (25-27 August 2010) that produced more than 50 mm of precipitation in De Bilt, the Netherlands, is analyzed using radar, rain gauge and disdrometer data. Without any correction, it is found that the radar severely underestimates the total rain amount (by more than 50 %). The calibration of the radar receiver is operationally monitored by analyzing the received power from the sun. This turns out to cause a 1 dB underestimation. The operational clutter filter applied by KNMI is found to incorrectly identify precipitation as clutter, especially at near-zero Doppler velocities. An alternative simple clutter removal scheme using a clear sky clutter map improves the rainfall estimation slightly. To investigate the effect of wet-radome attenuation, stable returns from buildings close to the radar are analyzed. It is shown that this may have caused an underestimation of up to 4 dB. Finally, a disdrometer is used to derive event and intra-event specific Z-R relations due to variations in the observed DSDs. Such variations may result in errors when applying the operational Marshall-Palmer Z-R relation. Correcting for all of these effects has a large positive impact on the radar-derived precipitation estimates and yields a good match between radar QPE and gauge

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  14. 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.

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  20. Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

    NASA Astrophysics Data System (ADS)

    van de Beek, C. Z.; Leijnse, H.; Stricker, J. N. M.; Uijlenhoet, R.; Russchenberg, H. W. J.

    2009-09-01

    This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The high spatial (120 m) and temporal (16 s) resolution of the radar combined with the extent of the database make this study a climatological analysis of the potential for high-resolution rainfall measurement with non-polarimetric X-band radar over completely flat terrain. An appropriate radar reflectivity - rain rate relation is derived from measurements of raindrop size distributions and compared with radar - rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

  1. Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

    NASA Astrophysics Data System (ADS)

    van de Beek, C. Z.; Leijnse, H.; Stricker, J. N. M.; Uijlenhoet, R.; Russchenberg, H. W. J.

    2010-02-01

    This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m) and temporal (16 s) resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity - rain rate relation is derived from measurements of raindrop size distributions and compared with radar - rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

  2. Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

    NASA Astrophysics Data System (ADS)

    van de Beek, C. Z.; Leijnse, H.; Stricker, J. N. M.; Uijlenhoet, R.; Russchenberg, H. W. J.

    2010-05-01

    This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m) and temporal (16 s) resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity - rain rate relation is derived from measurements of raindrop size distributions and compared with radar - rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

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

    NASA Astrophysics Data System (ADS)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2010-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2002-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

  6. 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

  7. Nowcasting for a high-resolution weather radar network

    NASA Astrophysics Data System (ADS)

    Ruzanski, Evan

    Short-term prediction (nowcasting) of high-impact weather events can lead to significant improvement in warnings and advisories and is of great practical importance. Nowcasting using weather radar reflectivity data has been shown to be particularly useful. The Collaborative Adaptive Sensing of the Atmosphere (CASA) radar network provides high-resolution reflectivity data amenable to producing valuable nowcasts. The high-resolution nature of CASA data requires the use of an efficient nowcasting approach, which necessitated the development of the Dynamic Adaptive Radar Tracking of Storms (DARTS) and sinc kernel-based advection nowcasting methodology. This methodology was implemented operationally in the CASA Distributed Collaborative Adaptive Sensing (DCAS) system in a robust and efficient manner necessitated by the high-resolution nature of CASA data and distributed nature of the environment in which the nowcasting system operates. Nowcasts up to 10 min to support emergency manager decision-making and 1--5 min to steer the CASA radar nodes to better observe the advecting storm patterns for forecasters and researchers are currently provided by this system. Results of nowcasting performance during the 2009 CASA IP experiment are presented. Additionally, currently state-of-the-art scale-based filtering methods were adapted and evaluated for use in the CASA DCAS to provide a scale-based analysis of nowcasting. DARTS was also incorporated in the Weather Support to Deicing Decision Making system to provide more accurate and efficient snow water equivalent nowcasts for aircraft deicing decision support relative to the radar-based nowcasting method currently used in the operational system. Results of an evaluation using data collected from 2007--2008 by the Weather Service Radar-1988 Doppler (WSR-88D) located near Denver, Colorado, and the National Center for Atmospheric Research Marshall Test Site near Boulder, Colorado, are presented. DARTS was also used to study the

  8. 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....

  9. 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....

  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, 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....

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

    PubMed

    Collier, C G

    2002-07-15

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

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

    PubMed

    Collier, C G

    2002-07-15

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

  15. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-01-01

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

  17. Automation of Cn2 profile extraction from weather radar images

    NASA Astrophysics Data System (ADS)

    Burchett, Lee R.; Fiorino, Steven T.; Buchanan, Matthew

    2012-06-01

    A novel method for measuring the structure constant of the atmospheric turbulence on an arbitrary path has recently been demonstrated by the Air Force Institute of Technology (AFIT). This method provides a unique ability to remotely measure the intensity of turbulence, which is important for predicting beam spread, wander, and scintillation effects on High Energy Laser (HEL) propagation. Because this is a new technique, estimating A novel method for measuring the structure constant of the atmospheric turbulence on an arbitrary path has recently been demonstrated by the Air Force Institute of Technology (AFIT). This method provides a unique ability to remotely measure the intensity of turbulence, which is important for predicting beam spread, wander, and scintillation effects on High Energy Laser (HEL) propagation. Because this is a new technique, estimating Cn2 using radar is a complicated and time consuming process. This paper presents a new software program which is being developed to automate the calculation of Cn2 over an arbitrary path. The program takes regional National Weather Service NEXRAD radar reflectivity measurements and extracts data for the path of interest. These reflectivity measurements are then used to estimate Cn2 over the path. The program uses the Radar Software Library (RSL) produced by the Tropical Rainfall Measuring Mission (TRMM) at the NASA/Goddard Flight Center. RSL provides support for nearly all formats of weather radar data. The particular challenge to extracting data is in determining which data bins the path passes through. Due to variations in radar systems and measurement conditions, the RSL produces data grids that are not consistent in geometry or completeness. The Cn2 program adapts to the varying geometries of each radar image. Automation of the process allows for fast estimation of Cn2 and supports a goal of real-time remote turbulence measurement. Recently, this software was used to create comparison data for RF

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Aghakouchak, A.; Habib, E.

    2008-05-01

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

  3. Sensitivity Studies of the Radar-Rainfall Error Models

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

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

  4. Radar subpixel-scale rainfall variability and uncertainty: a lesson learned from observations of a dense rain-gauge network

    NASA Astrophysics Data System (ADS)

    Peleg, N.; Ben-Asher, M.; Morin, E.

    2013-01-01

    Hydrological models for runoff estimations and flash-flood predictions are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires improving our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges, containing 27 gauges covering an area of about 4 km2, was installed near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability in remote-sensing at subpixel-scale resolution. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar. The gauge-rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The zero-distance correlation between rain gauges was high (0.92 on the 1-min scale) and increased as the time scale increased. The variance of the differences between radar pixel rainfall and averaged point rainfall (the variance reduction factor - VRF) was 1.6%, as measured for the 1-min scale. It was also found that at least four uniformly distributed rain stations are needed to represent the rainfall on the radar pixel scale. The radar-rain gauge error was mainly derived from radar estimation errors as the gauge sampling error contributed up to 22% to the total error. The radar rainfall estimations improved with increasing time scale and the radar-to-true rainfall ratio decreased with increasing time scale. Rainfall measurements collected with this network of rain gauges in the coming years will be used for further examination of rainfall's spatial and temporal variability.

  5. 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

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

    SciTech Connect

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

    1993-03-01

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

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    EPA Science Inventory

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

  10. 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...

  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, 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...

  13. 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...

  14. 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...

  15. 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

  16. 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

  17. Local Area Weather Radar in Alpine Setting

    NASA Astrophysics Data System (ADS)

    Savina, M.

    2012-04-01

    Space-time variability of precipitation in orographically complex regions is a challenging research topic. The difficult accessibility of remote regions and the high elevations make difficult the operation of conventional raingauges and reduce the visibility of large scale radars. A solution to this limitation might be the use of a number of cost-effective short-range X-band radars as complement to raingauges and conventional, large and expensive weather radars. This paper presents the results of a pilot experiment, which aimed at i) developing and assessing the performance of a cost-effective X-band Local Area Weather Radar (LAWR) located in the orographically complex Alpine region and ii) testing whether it could lead to better understanding of the nature of the precipitation process, e.g. identifying any possible dependence between precipitation and topography. The LAWR was deployed between August 2007 and October 2011 on the summit of the Kl. Matterhorn, located in the Swiss Alps at 3883 m a.s.l. (Valais, Switzerland). This was the first time that a cost-effective X-band radar was installed at such elevation and could be tested in operation-like conditions. Beside the technological improvements that were necessary for a reliable functioning of the LAWR hardware, much effort went into the development of a set of radar corrections and into the design of a new Alpine Radar COnversion Model (ARCOM), which includes the algorithms necessary to convert radar received echoes into precipitation rates, specifically accounting for the presence of the pronounced topography. The ARCOM was developed and tested on the basis of a set of precipitation events for which precipitation was measured also by 43 automatic raingauges located within 60 km range from the radar antenna. Conversely to the state-of-the-art conversion models, ARCOM accounts not only for the seasonal climatological condition but also of geometric and orographic forcings such as partial beam filling and beam

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

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

    Code of Federal Regulations, 2010 CFR

    2010-01-01

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

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

    Code of Federal Regulations, 2011 CFR

    2011-01-01

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

  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 large, transport category aircraft in passenger-carrying operations unless approved airborne...

  3. 14 CFR 135.175 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

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

  4. 14 CFR 135.175 - Airborne weather radar equipment requirements.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko

    2016-04-01

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

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2000-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Wei, Chih-Chiang

    2014-06-01

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

  13. Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts

    NASA Astrophysics Data System (ADS)

    Mittermaier, M. P.

    2008-05-01

    A simple measure of the uncertainty associated with using radar-derived rainfall estimates as "truth" has been introduced to the Numerical Weather Prediction (NWP) verification process to assess the effect on forecast skill and errors. Deterministic precipitation forecasts from the mesoscale version of the UK Met Office Unified Model for a two-day high-impact event and for a month were verified at the daily and six-hourly time scale using a spatially-based intensity-scale method and various traditional skill scores such as the Equitable Threat Score (ETS) and log-odds ratio. Radar-rainfall accumulations from the UK Nimrod radar-composite were used. The results show that the inclusion of uncertainty has some effect, shifting the forecast errors and skill. The study also allowed for the comparison of results from the intensity-scale method and traditional skill scores. It showed that the two methods complement each other, one detailing the scale and rainfall accumulation thresholds where the errors occur, the other showing how skillful the forecast is. It was also found that for the six-hourly forecasts the error distributions remain similar with forecast lead time but skill decreases. This highlights the difference between forecast error and forecast skill, and that they are not necessarily the same.

  14. Influences of weather phenomena on automotive laser radar systems

    NASA Astrophysics Data System (ADS)

    Rasshofer, R. H.; Spies, M.; Spies, H.

    2011-07-01

    Laser radar (lidar) sensors provide outstanding angular resolution along with highly accurate range measurements and thus they were proposed as a part of a high performance perception system for advanced driver assistant functions. Based on optical signal transmission and reception, laser radar systems are influenced by weather phenomena. This work provides an overview on the different physical principles responsible for laser radar signal disturbance and theoretical investigations for estimation of their influence. Finally, the transmission models are applied for signal generation in a newly developed laser radar target simulator providing - to our knowledge - worldwide first HIL test capability for automotive laser radar systems.

  15. 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

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

    NASA Technical Reports Server (NTRS)

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

    1997-01-01

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

  17. Radar subpixel-scale rainfall variability and uncertainty: lessons learned from observations of a dense rain-gauge network

    NASA Astrophysics Data System (ADS)

    Peleg, N.; Ben-Asher, M.; Morin, E.

    2013-06-01

    Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge-rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5%) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications

  18. Analysis of Surface and Radar Rainfall Observations during Two Tropical Systems in South Louisiana

    NASA Astrophysics Data System (ADS)

    Habib, E.; Tokay, A.; Meselhe, E.; Malakpet, C.

    2006-05-01

    This study presents comparative analyses on rainfall observations made during two tropical systems that affected south Louisiana: tropical storm Matthew in October 2004, and Hurricane Rita in September 2005. Storm Matthew formed from a tropical wave in the southwestern Gulf of Mexico on October 6th and made landfall on south Louisiana on October 10th causing as much as 10 inches of rain. Hurricane Rita developed on September 18th from a tropical depression and tracked westward into the Gulf of Mexico to reach category 5-strength on September 21st. Rita made landfall at the Texas/Louisiana border on 24th causing as much as 8-9 inches of rain. The current study focuses on analysis of rainfall observations during these two storms using a combination of surface-based and weather radar measurements. The results are based on analyses of small-scale variability of rainfall collected using a dense network of rain gauges in south Louisiana which includes a total of 13 dual rain gauge sites. In addition, an impact-type disdrometer is used to examine the raindrop size spectra characteristics during the two storms. The study will also compare data from the Lake Charles WSR-88D Level II volume scan reflectivity observations to gauge and disdrometer estimates. Implications for the ability of the WSR-88D radar to accurately measure rainfall during these two tropical systems will be investigated and discussed.

  19. Close-range radar rainfall estimation and error analysis

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  20. 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

  1. Multiscale Hydrologic Evaluation of Radar Rainfall for Flow Simulations

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2000-08-01

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

  4. 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. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  7. Mapping wintering waterfowl distributions using weather surveillance radar.

    PubMed

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

    2012-01-01

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

  8. Mapping wintering waterfowl distributions using weather surveillance radar

    USGS Publications Warehouse

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

    2012-01-01

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

  9. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  12. Comparison Between Radar and Automatic Weather Station Refractivity Variability

    NASA Astrophysics Data System (ADS)

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

    2016-08-01

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

  13. 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

  14. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

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

    PubMed

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

    2013-01-01

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

  17. Modeling Streamflow Using Gauge-Only Versus Radar-derived Rainfall

    NASA Astrophysics Data System (ADS)

    Sullivan, J. L.; Fuelberg, H. E.; Martinaitis, S. M.

    2007-12-01

    Rainfall in Florida is very dynamic in nature and is the greatest determining factor in hydrologic modeling studies. These studies traditionally have used gauge-only rainfall estimates despite their limitations and the advances in multi-sensor precipitation estimates. The convenience and familiarity with gauge data are a major factor leading to their continued use; however, there also have been questions about the statistical consistency and quality of radar-derived precipitation data. We previously reported on an intercomparison between gauge-only Thiessen polygon data with the gridded 4 × 4 km Florida State University (FSU) version of the National Weather Service (NWS) Multi-sensor Precipitation Estimator (MPE) scheme over several Florida basins. We showed that gauge-density within a basin is highly correlated with the magnitude of rainfall differences between the two datasets. The study also showed that seasonal characteristics of rainfall are an important factor leading to differences. The current paper evaluates the impacts of these input differences on streamflow by using a specialized, fully-distributed hydrologic model--the Watershed Assessment Model (WAM). Although WAM can model various water quality parameters, we focus on the streamflow produced by the different rainfall inputs. By describing differences in streamflow, we provide results that modelers can easily relate to--the impact of higher-resolution MPE rainfall data on their model's bottom-line. We have modeled the Suwannee River basin in North Florida between 1996 and 2005. Hourly rain gauge data used as input to the FSU MPE scheme were obtained from the National Climatic Data Center (NCDC) and the Suwannee River Water Management District (SRWMD). This combination provides the most reliably-dense gauge network possible. All of the rain gauge data were quality-controlled by FSU. Quality-controlled radar data were obtained from the NWS's Southeast River Forecast Center (SERFC). The FSU 4 × 4 km

  18. 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.

  19. 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

  20. Radar-based rainfall thresholds for debris flow warning: A review of opportunities, effect of estimation uncertainties, and assessment of key challenges

    NASA Astrophysics Data System (ADS)

    Marra, F.; Nikolopoulos, E.; Borga, M.; Creutin, J. D.

    2013-12-01

    The increasing availability of weather radar precipitation products provides new opportunities to improve upon existing methods for debris flow warning. The aim of this work is to examine how different characteristics of precipitation products, derived either from raingauges or from weather radar, may impact on the identification and use of precipitation thresholds that are used for debris flow warning. Precipitation exhibits space and time variability at all scales leading to high uncertainty in raingauge-based rain estimation. One distinct feature of the precipitation estimation problem for raingauge-based threshold relationship identification and use, is that the triggering precipitation to be estimated at the debris flow location exceeds an actual threshold which is likely not to be exceeded at the measuring raingauges. Recent results has shown that these characteristics may lead to biased precipitation threshold identification and low warning efficiency. Weather radar monitoring represent an interesting alternative for precipitation threshold identification, overcoming the sampling problem of point measurements. However, despite long-standing efforts, radar derived estimates are still affected by considerable uncertainties, particularly in the rough topography terrain typical of debris flows. It is therefore important to understand how uncertainties due to either rainfall sampling (typical of raingauges) or to rainfall estimation (typical of weather radar) propagates through the precipitation threshold identification methodology. Results are presented for a set of 10 high intensity debris-flow triggering storms that impacted the Southern Tyrol Region (Eastern Italian Alps) during the last decade. The region is characterized by rough orography, with elevation ranging from 300 to 4000 m asl, and it is monitored by a raingauge network with an average density of 1/70 km2 and a well calibrated and maintained C-band Doppler radar. High quality radar rainfall

  1. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    2013-10-08

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

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

    SciTech Connect

    Ortega, Edwin Campos

    2013-10-08

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-11-01

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

  7. 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.

  8. 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

  9. Improving the early-warning of a mud-debris flow using radar rainfall data

    NASA Astrophysics Data System (ADS)

    Jun, Hwandon; Kim, Soojun; Lee, Jiho

    2016-04-01

    The timely and accurate warning of mud-debris flows including landslide hazards is very important to protect life and property. The rainfall estimation uncertainty makes it difficult to issue accurate warning. Traditionally rain gauges have been the main source of surface rainfall measurements. The rain gauges provide an accurate point rainfall estimates, but their spatial resolution is limited by the low-density of a gauge network. The errors associated with interpolation schemes to fill in the missing data over the ungauged sites can introduce significant error due to the long distance between the rain gauge stations and the hazard site (ungauged sites), particularly over rough terrain. The radar system can provide rainfall information at higher temporal and spatial resolutions than was previously possible from rain gauge measurements. While radar provides accurate spatial and temporal resolution of the rainfall field at significant heights above the surface of the earth, numerous measurement errors can result in an inaccurate rainfall depth at the ground. This study attempts to improve mud-debris flow early-warnings through accurate rainfall depth estimation by applying an innovative artificial neural network method. The first scenario uses the nearest rainfall observing site from an ungauged hazard site. The second uses the radar rainfall data and improves the rainfall estimation compared to the first scenario. The third scenario integrates the above two scenarios using both radar and observed rainfall at the sites around the ungauged hazard site, and improves the rainfall estimation by the largest margin. This methodology is applied to the Seoul metropolitan area. The proposed methodology can be applied to improve the confidence in the early-warning of the mud-debris flow hazard in other areas. Acknowledgment This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by Ministry of Land, Infrastructure and

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

    NASA Astrophysics Data System (ADS)

    Chumchean, Siriluk; Seed, Alan; Sharma, Ashish

    2008-12-01

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

  12. A 10 cm dual frequency Doppler weather radar. Part 1: The radar system

    NASA Astrophysics Data System (ADS)

    Bishop, A. W.; Armstrong, G. M.

    1982-10-01

    Design concepts and test results are summarized for a Doppler weather radar system suitable for precipitation measurements over a wide span of radial velocities and slant ranges, even in the presence of ground clutter. The radar transmits two uniform pulse trains at 2.710 and 2.760 GHz. Uniformly spaced pulses permit ground clutter cancellation of up to 50 dB to be achieved with a three-pole elliptic filter. Pulse spacing at one frequency is consistent with long-range coverage in reflectivity, while spacing of the second is consistent with a wide unambiguous velocity measurement span.

  13. 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.

  14. Comparison of the TRMM Precipitation Radar rainfall estimation with ground-based disdrometer and radar measurements in South Greece

    NASA Astrophysics Data System (ADS)

    Ioannidou, Melina P.; Kalogiros, John A.; Stavrakis, Adrian K.

    2016-11-01

    The performance of the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) rainfall estimation algorithm is assessed, locally, in Crete island, south Greece, using data from a 2D-video disdrometer and a ground-based, X-band, polarimetric radar. A three-parameter, normalized Gamma drop size distribution is fitted to the disdrometer rain spectra; the latter are classified in stratiform and convective rain types characterized by different relations between distribution parameters. The method of moments estimates more accurately the distribution parameters than the best fit technique, which exhibits better agreement with and is more biased by the observed droplet distribution at large diameter values. Power laws between the radar reflectivity factor (Z) and the rainfall rate (R) are derived from the disdrometer data. A significant diversity of the prefactor and the exponent of the estimated power laws is observed, depending on the scattering model and the regression technique. The Z-R relationships derived from the disdrometer data are compared to those obtained from TRMM-PR data. Generally, the power laws estimated from the two datasets are different. Specifically, the greater prefactor found for the disdrometer data suggests an overestimation of rainfall rate by the TRMM-PR algorithm for light and moderate stratiform rain, which was the main rain type in the disdrometer dataset. Finally, contemporary data from the TRMM-PR and a ground-based, X-band, polarimetric radar are analyzed. Comparison of the corresponding surface rain rates for a rain event with convective characteristics indicates a large variability of R in a single TRMM-PR footprint, which typically comprises several hundreds of radar pixels. Thus, the coarse spatial resolution of TRMM-PR may lead to miss of significant high local peaks of convective rain. Also, it was found that the high temporal variability of convective rain may introduce significant errors in the estimation of bias of

  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

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

    NASA Astrophysics Data System (ADS)

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

    2004-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Licznar, Paweł; 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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    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.

  19. 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.

  20. 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  2. Rainfall estimation using raingages and radar — A Bayesian approach: 1. Derivation of estimators

    NASA Astrophysics Data System (ADS)

    Seo, D.-J.; Smith, J. A.

    1991-03-01

    Procedures for estimating rainfall from radar and raingage observations are constructed in a Bayesian framework. Given that the number of raingage measurements is typically very small, mean and variance of gage rainfall are treated as uncertain parameters. Under the assumption that log gage rainfall and log radar rainfall are jointly multivariate normal, the estimation problem is equivalent to lognormal co-kriging with uncertain mean and variance of the gage rainfall field. The posterior distribution is obtained under the assumption that the prior for the mean and inverse of the variance of log gage rainfall is normal-gamma 2. Estimate and estimation variance do not have closed-form expressions, but can be easily evaluated by numerically integrating two single integrals. To reduce computational burden associated with evaluating sufficient statistics for the likelihood function, an approximate form of parameter updating is given. Also, as a further approximation, the parameters are updated using raingage measurements only, yielding closed-form expressions for estimate and estimation variance in the Gaussian domain. With a reduction in the number of radar rainfall data in constructing covariance matrices, computational requirements for the estimation procedures are not significantly greater than those for simple co-kriging. Given their generality, the estimation procedures constructed in this work are considered to be applicable in various estimation problems involving an undersampled main variable and a densely sampled auxiliary variable.

  3. Snowfall variability as seen by a weather radar

    NASA Astrophysics Data System (ADS)

    Berne, A.

    2014-12-01

    Snowfall is highly variable in space and time because of the interactions between (cold) cloud microphysics and turbulent atmospheric dynamics. In comnplex terrain, this variability is amplified but remains poorly understood mainly due to a lack of monitoring capabilities. This contribution deals with the characterization and the quantification of the variability of snowfall at small scales (up to 10 km) in the Swiss Alps as seen by a Doppler polarimetric weather radar.The focus is first on the comparison of the horizontal variability in snowfall close to the surface (as seen by a radar) and in the snow accumulation on the ground (derived from aerial laser scans). The results show that the latter is larger than the former, pointing towards small-scale topographically induced winds as the main factor controlling the variability of snow accumulation. Second, the average vertical structure of snowfall is investigated using the polarimetric radar variables collected in vertical scans in the atmosphere. The main features of the vertical structure are related to the dominant microphysical processes at work.These results are a (preliminray) step forward to better understand the variability of snowfall at small scales in complex terrain, and illustrate the need for additional effort to collect snowfall observations from a variety of sensors

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

    NASA Technical Reports Server (NTRS)

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

    1991-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  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

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

    NASA Technical Reports Server (NTRS)

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

    1998-01-01

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

  9. 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.

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

  12. 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.

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

    NASA Technical Reports Server (NTRS)

    Larsen, M. F.

    1983-01-01

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

  14. 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

  15. 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.

  16. 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.

  17. Impact of radar-rainfall error structure on estimated flood magnitude across scales: An investigation based on a parsimonious distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Cunha, Luciana K.; Mandapaka, Pradeep V.; Krajewski, Witold F.; Mantilla, Ricardo; Bradley, Allen A.

    2012-10-01

    The goal of this study is to diagnose the manner in which radar-rainfall input affects peak flow simulation uncertainties across scales. We used the distributed physically based hydrological model CUENCAS with parameters that are estimated from available data and without fitting the model output to discharge observations. We evaluated the model's performance using (1) observed streamflow at the outlet of nested basins ranging in scale from 20 to 16,000 km2 and (2) streamflow simulated by a well-established and extensively calibrated hydrological model used by the US National Weather Service (SAC-SMA). To mimic radar-rainfall uncertainty, we applied a recently proposed statistical model of radar-rainfall error to produce rainfall ensembles based on different expected error scenarios. We used the generated ensembles as input for the hydrological model and summarized the effects on flow sensitivities using a relative measure of the ensemble peak flow dispersion for every link in the river network. Results show that peak flow simulation uncertainty is strongly dependent on the catchment scale. Uncertainty decreases with increasing catchment drainage area due to the aggregation effect of the river network that filters out small-scale uncertainties. The rate at which uncertainty changes depends on the error structure of the input rainfall fields. We found that random errors that are uncorrelated in space produce high peak flow variability for small scale basins, but uncertainties decrease rapidly as scale increases. In contrast, spatially correlated errors produce less scatter in peak flows for small scales, but uncertainty decreases slowly with increasing catchment size. This study demonstrates the large impact of scale on uncertainty in hydrological simulations and demonstrates the need for a more robust characterization of the uncertainty structure in radar-rainfall. Our results are diagnostic and illustrate the benefits of using the calibration-free, multiscale

  18. 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.

  19. Airborne laser scan data: a valuable tool with which to infer weather radar partial beam blockage in urban environments

    NASA Astrophysics Data System (ADS)

    Cremonini, Roberto; Moisseev, Dmitri; Chandrasekar, Venkatachalam

    2016-10-01

    High-spatial-resolution weather radar observations are of primary relevance for hydrological applications in urban areas. However, when weather radars are located within metropolitan areas, partial beam blockages and clutter by buildings can seriously affect the observations. Standard simulations with simple beam propagation models and digital elevation models (DEMs) are usually not able to evaluate buildings' contribution to partial beam blockages. In recent years airborne laser scanners (ALSs) have evolved to the state-of-the-art technique for topographic data acquisition. Providing small footprint diameters (10-30 cm), ALS data allow accurate reconstruction of buildings and forest canopy heights. Analyzing the three weather C-band radars located in the metropolitan area of Helsinki, Finland, the present study investigates the benefits of using ALS data for quantitative estimations of partial beam blockages. The results obtained applying beam standard propagation models are compared with stratiform 24 h rainfall accumulation to evaluate the effects of partial beam blockages due to constructions and trees. To provide a physical interpretation of the results, the detailed analysis of beam occultations is achieved by open spatial data sets and open-source geographic information systems.

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

    USGS Publications Warehouse

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

    1999-01-01

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

  1. 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.

  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-Φ gram, rainfall, sea level pressure, vorticity and vertical velocity are studied. Results show that while there are differences of 2-3 hours between the observed and simulated time of the storms, the distances between observed and simulated locations of the storms are several tens of kilometers. The maximum CAPE was generally above 2400 J kg-1 in the case. The maximum intensity of surface wind speed simulated by the model was only 38 m sec-1. This seems to be underestimated. The highest vertical velocity (updraft) simulated by the model was 250 m sec-1 around 800-950 hPa. The updraft reached up to 150 hPa. It seems that the funnel vortex reached the ground, and might have passed some places a few meters above the surface. According to the Fujita Pearson scale, this tornado can be classified as F-2 with estimated wind speed of 50-70 ms-1. Keywords: Tornado, DWR, NCEP-FNL, T-Φ gram, CAPE.

  3. 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

  4. 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.

  5. Spectral analyses of the dual polarization Doppler weather radar data

    NASA Astrophysics Data System (ADS)

    Bachmann, Svetlana Monakhova

    2007-12-01

    Echoes in clear air from biological scatterers mixed within the resolution volumes over a large region are presented. These echoes were observed with the polarimetric prototype of the forthcoming WSR-88D weather radar. The study case occurred in the evening of September 7, 2004, at the beginning of the bird migrating season. Novel polarimetric spectral analyses are used for distinguishing signatures of birds and insects in multimodal spectra. These biological scatterers were present at the same time in the radar resolution volumes over a large area. Spectral techniques for (1) data censoring, (2) wind retrieval and (3) estimation of intrinsic values/functions of polarimetric variables for different types of scatterers are presented. The technique for data censoring in the frequency domain allows detection of weak signals. Censoring is performed on the level of spectral densities, allowing exposure of contributions to the spectrum from multiple types of scatterers. The spectral techniques for wind retrieval allow simultaneous estimation of wind from the data that are severely contaminated by migrating birds, and assessment of bird migration parameters. The intrinsic polarimetric signatures associated with the variety of scatterers can be evaluated using presented methodology. Algorithms for echo classification can be built on these. The possibilities of spectral processing using parametric estimation techniques are explored for resolving contributions to the Doppler spectrum from the three types of scatterers: passive wind tracers, actively flying insects and birds. A combination of parametric and non-parametric polarimetric spectral analyses is used to estimate the small bias introduced to the wind velocity by actively flying insects.

  6. Validation of GOES-R Rainfall Rate Algorithm through TRMM PR and NIMROD radars

    NASA Astrophysics Data System (ADS)

    Li, Y.; Kuligowski, R. J.

    2010-12-01

    The next generation Geostationary Operational Environmental Satellite (GOES-R) series will offer a continuation of current products and services and enable improved and new capabilities. The Advanced Baseline Imager (ABI) onboard the GOES-R platform has been designed to offer improved spatial and spectral resolution and temporal sampling, all of which should lead to enhanced capabilities for satellite-based rainfall estimation. The Hydrology Algorithm Team in the GOES-R Algorithm Working Group (AWG) has recommended, developed, and demonstrated an algorithm for the operational rainfall rate product, the GOES-R version of Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) algorithm. SCaMPR is an effort to combine the relative strengths of infrared (IR)-based and microwave (MW)-based estimates of precipitation. The GOES-R version of SCaMPR currently runs over Europe and Africa and surrounding oceans using the METEOSAT Spinning Enhanced Visible Infra-Red Imager (SEVIRI) data as a proxy for the ABI. Because the algorithm produces a field of instantaneous rainfall rates, radar data (both space-based and ground-based) is the only available source of data for validation against spec. Comparisons are made against Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data and Nimrod radar data over Western Europe obtained from the British Atmospheric Data Centre (BADC), respectively. This presentation will introduce the analysis methodology for estimating the precision and accuracy and provide the quantitative results in terms of the Functional and Performance Specifications.

  7. 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.

  8. Simulations of Dual-Frequency Radar Rainfall Retrievals

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  10. Minimum operational performance standards for airborne weather and ground mapping pulsed radars

    NASA Astrophysics Data System (ADS)

    1980-11-01

    Minimum operational performance standards for airborne weather and ground mapping pulsed radars, including both air carrier and large aircraft-type radar systems, are described. Those requirements and technologies pertinent to general aviation, where limitations on space and/or weight may apply are taken into account.

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

    NASA Astrophysics Data System (ADS)

    Amitai, Eyal

    2000-12-01

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

  12. 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

  13. 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.

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Avsar, Ercument

    2016-07-01

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

  16. 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.

  17. Rainfall rate measurement with a polarimetric radar at an attenuated wavelength

    NASA Astrophysics Data System (ADS)

    Sauvageot, Henri; Mesnard, Frédéric; Illingworth, Anthony J.; Goddard, John W. F.

    Among the many ways investigated for radar estimation of rainfall, polarimetric methods are the most promising. However most polarimetric algorithms are degraded by attenuation by precipitation and clouds and by calibration error. A new method was recently proposed in which the differential polarimetric attenuation is used to perform an accurate rain rate measurement. The method is independent of the radar calibration and of the attenuation by undetected clouds. This algorithm is also usable as a qualitative hail detector, as well as a detector of anomalous propagation. The goal of the paper is to describe the results of the first experimental implementation of this method using the 35 GHz RABELAIS radar, as attenuated radar, and the 3 GHz CAMRa radar as a reference. We show that the proposed algorithm is stable and enables us to retrieve the actual rain rate even from an observed signal attenuated by more than 30 dB. The results are insensitive to the value used for the power coefficient of the Z(R) relation.

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

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  19. Linking ENSO and heavy rainfall events over coastal British Columbia through a weather pattern classification

    NASA Astrophysics Data System (ADS)

    Brigode, P.; Mićović, Z.; Bernardara, P.; Paquet, E.; Garavaglia, F.; Gailhard, J.; Ribstein, P.

    2013-04-01

    Classifications of atmospheric weather patterns (WPs) are widely used for the description of the climate of a given region and are employed for many applications, such as weather forecasting, downscaling of global circulation model outputs and reconstruction of past climates. WP classifications were recently used to improve the statistical characterisation of heavy rainfall. In this context, bottom-up approaches, combining spatial distribution of heavy rainfall observations and geopotential height fields have been used to define WP classifications relevant for heavy rainfall statistical analysis. The definition of WPs at the synoptic scale creates an interesting variable which could be used as a link between the global scale of climate signals and the local scale of precipitation station measurements. We introduce here a new WP classification centred on the British Columbia (BC) coastal region (Canada) and based on a bottom-up approach. Five contrasted WPs composed this classification, four rainy WPs and one non-rainy WP, the anticyclonic pattern. The four rainy WPs are mainly observed in the winter months (October to March), which is the period of heavy precipitation events in coastal BC and is thus consistent with the local climatology. The combination of this WP classification with the seasonal description of rainfall is shown to be useful for splitting observed precipitation series into more homogeneous sub-samples (i.e. sub-samples constituted by days having similar atmospheric circulation patterns) and thus identifying, for each station, the synoptic situations that generate the highest hazard in terms of heavy rainfall events. El Niño-Southern Oscillations (ENSO) significantly influence the frequency of occurrence of two coastal BC WPs. Within each WP, ENSO seem to influence only the frequency of rainy events and not the magnitudes of heavy rainfall events. Consequently, heavy rainfall estimations do not show significant evolution of heavy rainfall

  20. 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.

  1. 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

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  5. 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.

  6. Dual-polarization radar rainfall estimation in Korea according to raindrop shapes obtained by using a 2-D video disdrometer

    NASA Astrophysics Data System (ADS)

    Kim, Hae-Lim; Suk, Mi-Kyung; Park, Hye-Sook; Lee, Gyu-Won; Ko, Jeong-Seok

    2016-08-01

    Polarimetric measurements are sensitive to the sizes, concentrations, orientations, and shapes of raindrops. Thus, rainfall rates calculated from polarimetric radar are influenced by the raindrop shapes and canting. The mean raindrop shape can be obtained from long-term raindrop size distribution (DSD) observations, and the shapes of raindrops can play an important role in polarimetric rainfall algorithms based on differential reflectivity (ZDR) and specific differential phase (KDP). However, the mean raindrop shape is associated with the variation of the DSD, which can change depending on precipitation types and climatic regimes. Furthermore, these relationships have not been studied extensively on the Korean Peninsula. In this study, we present a method to find optimal polarimetric rainfall algorithms for the Korean Peninsula by using data provided by both a two-dimensional video disdrometer (2DVD) and the Bislsan S-band dual-polarization radar. First, a new axis-ratio relation was developed to improve radar rainfall estimations. Second, polarimetric rainfall algorithms were derived by using different axis-ratio relations. The rain gauge data were used to represent the ground truth situation, and the estimated radar-point hourly mean rain rates obtained from the different polarimetric rainfall algorithms were compared with the hourly rain rates measured by a rain gauge. The daily calibration biases of horizontal reflectivity (ZH) and differential reflectivity (ZDR) were calculated by comparing ZH and ZDR radar measurements with the same parameters simulated by the 2DVD. Overall, the derived new axis ratio was similar to the existing axis ratio except for both small particles (≤ 2 mm) and large particles (≥ 5.5 mm). The shapes of raindrops obtained by the new axis-ratio relation carried out with the 2DVD were more oblate than the shapes obtained by the existing relations. The combined polarimetric rainfall relations using ZDR and KDP were more efficient than

  7. 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.

  8. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-10-01

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

  10. 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.

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

    NASA Astrophysics Data System (ADS)

    Grecu, Mircea; Anagnostou, Emmanouil N.

    2002-07-01

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

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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

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

    NASA Astrophysics Data System (ADS)

    Borga, M.; Creutin, J. D.

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Bernard, Martino; Gregoretti, Carlo

    2016-04-01

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

  2. 5 year radar-based rainfall statistics: disturbances analysis and development of a post-correction scheme for the German radar composite

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  3. 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.

  4. 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.

  5. Single event modelling in small catchments - the significance of operational C-band rainfall radar and paved terrain

    NASA Astrophysics Data System (ADS)

    Lange, J.; Wagner, A.; Tetzlaff, D.; Leibundgut, C.

    2003-04-01

    Owing to extensive networks of paved roads and drainage lines, the 1.7 km2 Loechernbach catchment, southwest Germany, responds almost instantaneously to high intensity rainfall events in summer. Existing tracerhydrological investigation proved the dominance of direct runoff components. To incorporate the necessary temporal and spatial resolution, raw data from an operational C-band rainfall radar are used as input for a spatially distributed rainfall-runoff model to analyse runoff generation during a series of three summer thunderstorms. While for the first event the radar is calibrated using data from a remote ground station only supplemented by one uncertain daily total inside the catchment, nine days later a newly installed ground station within the study catchment facilitates a more dependable radar calibration. Results suggest that for high resolution modelling of localised convective summer thunderstorms, operational C-band rainfall radars should be calibrated independently for every individual storm cell using station data (total volumes or intensity readings) from the immediate vicinity or from within the study catchment. To preserve the spatial detail of the rainfall radar it is necessary to maintain its original polar coordinate system. Independently calibrated for the two latter events of the series, the model correctly reproduces the two separate runoff peaks apparent in the runoff records of both events. These two peaks can be assigned to different source areas and the first of them yields runoff coefficients of only 30% for paved areas. Hence, the present model application suggests that in rural areas a large percentage of runoff from paved terrain may infiltrate into open areas nearby and that a gross simplification of paved surfaces as 100% runoff sources may be misleading in hydrological analyses.

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2011-10-01

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

  8. 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

  9. Flash Flood Modeling in Changing Hydrological Conditions Using a Hydrological Model and Radar Rainfall Data

    NASA Astrophysics Data System (ADS)

    Rozalis, S.; Price, C.; Yair, Y.; Morin, E.

    2009-04-01

    Flash floods are one of the most devastating natural disasters, causing much damage to property and can often lead to loss of human lives. This is a particular problem in the Mediterranean region. Understanding the meteorological and hydrological conditions for flash flood generation is an essential step on the way to forecast them and prevent some of the damage they might cause. The occurrence of a flood event is determined by meteorological conditions, producing large amounts of precipitation over a short period of time, as well as hydrological conditions, such as soil type, land cover and soil antecedent moisture conditions, which vary throughout the year and from place to place. The current study is a part of the FLASH research project (EU-FP6). In this work we use a hydrological model with data from twenty major flood events which occurred in the study area between 1991 and 2006, to better understand the role of changing hydrological and meteorological conditions in generating flash floods and in order to improve the prediction of future flash flood events. The model's runoff calculation is done by the Soil Conservation Service Curve Number method, taking into account antecedent soil moisture, land use and soil type. Runoff flow over hillslopes and channels is calculated by the Kinematic wave method. No calibration with measured flow data was performed. As rainfall data we use radar rainfall estimations adjusted to rain gauge along the basin. The model is applied over a 27 km2 basin located in a Mediterranean area in North-Eastern Israel with mean annual precipitation of about 450 mm. The main land use in this area is agriculture, with forests and orchards on the upper part and cultivated fields on its lower parts. We compare the model's runoff calculations with flow observations derived from a flow gauge located on the catchment outlet. The model allows us to explore the special synoptic, rainfall and surface conditions, responsible for the generation of

  10. Mass discharge rate retrieval combining weather radar and thermal camera observations

    NASA Astrophysics Data System (ADS)

    Vulpiani, Gianfranco; Ripepe, Maurizio; Valade, Sebastien

    2016-08-01

    The mass discharge rate is a key parameter for initializing volcanic ash dispersal models. Commonly used empirical approaches derive the discharge rate by the plume height as estimated by remote sensors. A novel approach based on the combination of weather radar observations and thermal camera imagery is presented here. It is based on radar ash concentration estimation and the retrieval of the vertical exit velocities of the explosive cloud using thermal camera measurements. The applied radar retrieval methodology is taken from a revision of previously presented work. Based on the analysis of four eruption events of the Mount Etna volcano (Sicily, Italy) that occurred in December 2015, the proposed methodology is tested using observations collected by three radar systems (at C and X band) operated by the Italian Department of Civil Protection. The total erupted mass was estimated to be about 9·109 kg and 2.4·109 kg for the first and second events, respectively, while it was about 1.2·109 kg for both the last two episodes. The comparison with empirical approaches based on radar-retrieved plume height shows a reasonably good agreement. Additionally, the comparative analysis of the polarimetric radar measurements provides interesting information on the vertical structure of the ash plume, including the size of the eruption column and the height of the gas thrust region.

  11. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2010-05-01

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

  13. Wind from Indian Doppler Weather Radars: a data assimilation view point

    NASA Astrophysics Data System (ADS)

    Dutta, Devajyoti; Mallick, Swapan; Jyothi, K. A.; George, John P.; Kumar, D. Preveen

    2016-05-01

    Doppler Weather Radar (DWR) can provide tropospheric wind observations with high temporal and spatial resolutions. The Volume Velocity Processing (VVP) technique is one of the processing methods which can provide vertical profiles of mean horizontal winds. The DWR observed VVP winds gives a continuous observation of the wind field at various atmospheric levels. The quality of the VVP winds is studied against the short-range forecast of the NCUM model (model background). The biases of the observation are calculated against model background. This study focuses on the quality of VVP winds and seasonal variation of bias of the observed wind. This results shows that the VVP winds provides reasonably accurate estimates of the vertical wind structure in the troposphere over radar locations which can be effectively used in the numerical weather prediction system.

  14. 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

  15. The scavenging of air pollutants by precipitation, and its estimation with the aid of weather radar

    NASA Astrophysics Data System (ADS)

    Jylha, Kirsti Tellervo

    2000-09-01

    Precipitation cleanses the air by capturing airborne pollutants and depositing them onto the ground. The efficiency of this process may be expressed by the fractional depletion rate of pollutant concentrations in the air, designated as the scavenging coefficient. It depends on the size distribution of the raindrops and snow crystals and is thereby related to quantities estimated by weather radar, namely, the radar reflectivity factor and the precipitation rate. On the other hand, there are no universal relationships between the scavenging coefficient and these two quantities; the relationships vary depending on the properties of the precipitation and pollutants. In the present thesis, a few estimates for them were derived theoretically and empirically, using in the latter case observations made in Finland either after the Chernobyl nuclear accident or during a wintertime case study near a coal-fired power plant. The greatest advantage in the use of weather radar in assessing precipitation scavenging arises from the fact that radar estimates the spatial distributions of precipitation in real time with a good spatial and temporal resolution. Radar software usually used to create displays of the precipitation rate can easily be modified to show distributions of the scavenging coefficient. Such images can provide valuable information about the areas where a substantial portion of the pollutants is deposited onto the ground or, alternatively, remains airborne. Based on the movement of the precipitation areas, it is also possible to make short-term forecasts of those areas most likely to be exposed to wet deposition. A network of radars may hence form an important part of a real-time monitoring and warning system that can be immediately effective in the event of an accidental releases of hazardous materials into the air.

  16. 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.

  17. 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

  18. 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

    2015-06-18

    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.

  19. 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

  20. Earthquake Weather: Linking Seismicity to Changes in Barometric Pressure, Earth Tides, and Rainfall

    NASA Astrophysics Data System (ADS)

    West, J. D.; Garnero, E.; Shirzaei, M.

    2015-12-01

    It has been widely observed that earthquakes can be triggered due to changes in stress induced by the passage of surface waves from remote earthquakes. These stress changes are typically on the order of a few kiloPascals and occur over time spans of seconds. Less well investigated is the question of whether triggering of seismic activity can result from similar stress changes occurring over periods of hours or days due to changing barometric pressure, rainfall, and Earth tides. Past studies have shown a possible link between these stress sources and slow earthquakes in Taiwan (Hsu et al., 2015). Here, we investigate the relationship between seismicity and changing barometric pressure, Earth tides, and rainfall for four regions of the western United States where regional seismic networks provide high-quality seismic catalogs over relatively long time periods: Southern California, Northern California, the Pacific Northwest, and Utah. For each region we obtained seismic catalogs from January 2001 through September 2014 and acquired hourly data for barometric pressure and rainfall across the regions from the National Climatic Data Center. The vertical stress time series due to Earth tides was computed for the location of each weather station in the study areas. We summed the stresses from these 3 sources and looked for variations in seismicity correlated to the stress changes. We show that seismicity rates increase with increasing magnitude of stress change. In many cases the increase in seismicity is larger for reductions in vertical stress than it is for stress increases. We speculate that the dependency of seismic rate on combined vertical stress is acting through a combination of two mechanisms: (1) Reduced stresses reduce the normal force on faults, triggering failure in critically-stressed faults. (2) Increased stresses may similarly reduce the normal force on faults due to increases in pore pressure induced in the fault region.

  1. Meteorite Falls Observed in U.S. Weather Radar Data in 2015 and 2016 (To Date)

    NASA Technical Reports Server (NTRS)

    Fries, Marc; Fries, Jeffrey; Hankey, Mike; Matson, Robert

    2016-01-01

    To date, over twenty meteorite falls have been located in the weather radar imagery of the National Oceanic and Atmospheric Administration (NOAA)'s NEXRAD radar network. We present here the most prominent events recorded since the last Meteoritical Society meeting, covering most of 2015 and early 2016. Meteorite Falls: The following events produced evidence of falling meteorites in radar imagery and resulted in meteorites recovered at the fall site. Creston, CA (24 Oct 2015 0531 UTC): This event generated 218 eyewitness reports submitted to the American Meteor Society (AMS) and is recorded as event #2635 for 2015 on the AMS website. Witnesses reported a bright fireball with fragmentation terminating near the city of Creston, CA, north of Los Angeles. Sonic booms and electrophonic noise were reported in the vicinity of the event. Weather radar imagery records signatures consistent with falling meteorites in data from the KMUX, KVTX, KHNX and KVBX. The Meteoritical Society records the Creston fall as an L6 meteorite with a total recovered mass of 688g. Osceola, FL (24 Jan 2016 1527 UTC): This daytime fireball generated 134 eyewitness reports on AMS report number 266 for 2016, with one credible sonic boom report. The fireball traveled roughly NE to SW with a terminus location north of Lake City, FL in sparsely populated, forested countryside. Radar imagery shows distinct and prominent evidence of a significant meteorite fall with radar signatures seen in data from the KJAX and KVAX radars. Searchers at the fall site found that recoveries were restricted to road sites by the difficult terrain, and yet several meteorites were recovered. Evidence indicates that this was a relatively large meteorite fall where most of the meteorites are unrecoverable due to terrain. Osceola is an L6 meteorite with 991 g total mass recovered to date. Mount Blanco, TX (18 Feb 2016 0343 UTC): This event produced only 39 eyewitness reports and is recorded as AMS event #635 for 2016. No

  2. Measurement of rainfall path attenuation near nadir: A comparison of radar and radiometer methods at 13.8 GHz

    NASA Astrophysics Data System (ADS)

    Durden, S. L.; Haddad, Z. S.; Im, E.; Kitiyakara, A.; Li, F. K.; Tanner, A. B.; Wilson, W. J.

    1995-07-01

    Rain profile retrieval from spaceborne radar is difficult because of the presence of attenuation at the higher frequencies planned for these systems. One way to reduce the ambiguity in the retrieved rainfall profile is to use the path-integrated attenuation as a constraint. Two techniques for measuring the path-integrated attenuation have been proposed: the radar surface reference technique and microwave radiometry. We compare these two techniques using data acquired by the Airborne Rain Mapping Radar (ARMAR) 13.8-GHz airborne radar and radiometer during the Tropical Ocean-Global Atmosphere Coupled Ocean Atmosphere Response Experiment (TOGA COARE) in the western Pacific Ocean in early 1993. The two techniques have a mean difference close to zero for both nadir and 10° incidence. The RMS difference is 1.4 dB and is reduced to 1 dB or less if points where the radiometer was likely saturated are excluded. Part of the RMS difference can be attributed to variability in the ocean surface cross section due to wind effects and possibly rain effects. The results presented here are relevant for the Tropical Rainfall Measuring Mission, which will include a 13.8-GHz precipitation radar.

  3. Spatial analysis of rainfall variation using variogram model parameters of X-band radar images in a small mountainous catchment

    NASA Astrophysics Data System (ADS)

    Guardiola-Albert, Carolina; Díez-Herrero, Andrés; Bodoque, José M.; Bermejo, Marcos; Rivero-Honegger, Carlos; Yagüe, Carlos; Monjo, Robert; Tapiador, Francisco J.

    2016-04-01

    The present study deals the rainfall spatial variability of a small mountainous catchment, which includes the spatial distribution and variability of convective and stratiform events. This work focuses on the precipitation events with hydrological response in Venero-Claro Basin (Avila, Spain). In this basin of 15 square kilometers, flood events of different magnitudes have been often registered. Therefore, any improvement in understanding rainfall characteristics in the area can be of special importance in rainfall estimation and hence to calibrate and validate hydrological models. These enhancements imply more objectivity of risk studies and more predictive and preventive capacity. To separate events by origin it has been used the dimensionless index defined by Monjo (2015), according to the relative temporal distribution of maximum intensities. The main advantages of this method are that it does not require thresholds, so it can be applied for each rain gauge. The geostatistical variogram tool is used to quantify the spatial characteristics of both kinds of events. Hourly rainfall accumulations over the area are computed with observations from one of the 5 existing X-band radar in Spain and 7 rain gauges located in the zone. For each hour the rainfall variogram model has been fitted with the aid of the X-band radar images. Valuable information is extracted from the stratiform and convective ensembles of variogram models. The variogram model parameters are analyzed to determine characteristics of spatial continuity that differentiates stratiform and convective events, and quartiles of sills and ranges in both ensembles are compared.

  4. Identifying Precipitation Types Using Dual-Polarization-Based Radar and Numerical Weather Prediction Model Data

    NASA Astrophysics Data System (ADS)

    Seo, B. C.; Bradley, A.; Krajewski, W. F.

    2015-12-01

    The recent upgrade of dual-polarization with NEXRAD radars has assisted in improving the characterization of microphysical processes in precipitation and thus has enabled precipitation estimation based on the identified precipitation types. While this polarimetric capability promises the potential for the enhanced accuracy in quantitative precipitation estimation (QPE), recent studies show that the polarimetric estimates are still affected by uncertainties arising from the radar beam geometry/sampling space associated with the vertical variability of precipitation. The authors, first of all, focus on evaluating the NEXRAD hydrometeor classification product using ground reference data (e.g., ASOS) that provide simple categories of the observed precipitation types (e.g., rain, snow, and freezing rain). They also investigate classification uncertainty features caused by the variability of precipitation between the ground and the altitudes where radar samples. Since this variability is closely related to the atmospheric conditions (e.g., temperature) at near surface, useful information (e.g., critical thickness and temperature profile) that is not available in radar observations is retrieved from the numerical weather prediction (NWP) model data such as Rapid Refresh (RAP)/High Resolution Rapid Refresh (HRRR). The NWP retrieved information and polarimetric radar data are used together to improve the accuracy of precipitation type identification at near surface. The authors highlight major improvements and discuss limitations in the real-time application.

  5. 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

  6. 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…

  7. 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

  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.; 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.

  9. Remote sensing of rainfall for debris-flow hazard assessment

    USGS Publications Warehouse

    Wieczorek, G.F.; Coe, J.A.; Godt, J.W.; ,

    2003-01-01

    Recent advances in remote sensing of rainfall provide more detailed temporal and spatial data on rainfall distribution. Four case studies of abundant debris flows over relatively small areas triggered during intense rainstorms are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. Three examples with rainfall estimates from National Weather Service Doppler radar and one example with rainfall estimates from infrared imagery from a National Oceanic and Atmospheric Administration satellite are compared with ground-based measurements of rainfall and with landslide distribution. The advantages and limitations of using remote sensing of rainfall for landslide hazard analysis are discussed. ?? 2003 Millpress,.

  10. 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.

  11. Extraction of convective cloud parameters from Doppler Weather Radar MAX(Z) product using Image Processing Technique

    NASA Astrophysics Data System (ADS)

    Arunachalam, M. S.; Puli, Anil; Anuradha, B.

    2016-07-01

    In the present work continuous extraction of convective cloud optical information and reflectivity (MAX(Z) in dBZ) using online retrieval technique for time series data production from Doppler Weather Radar (DWR) located at Indian Meteorological Department, Chennai has been developed in MATLAB. Reflectivity measurements for different locations within the DWR range of 250 Km radii of circular disc area can be retrieved using this technique. It gives both time series reflectivity of point location and also Range Time Intensity (RTI) maps of reflectivity for the corresponding location. The Graphical User Interface (GUI) developed for the cloud reflectivity is user friendly; it also provides the convective cloud optical information such as cloud base height (CBH), cloud top height (CTH) and cloud optical depth (COD). This technique is also applicable for retrieving other DWR products such as Plan Position Indicator (Z, in dBZ), Plan Position Indicator (Z, in dBZ)-Close Range, Volume Velocity Processing (V, in knots), Plan Position Indicator (V, in m/s), Surface Rainfall Intensity (SRI, mm/hr), Precipitation Accumulation (PAC) 24 hrs at 0300UTC. Keywords: Reflectivity, cloud top height, cloud base, cloud optical depth

  12. 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

  13. A radar-based regional extreme rainfall analysis to derive the thresholds for a novel automatic alert system in Switzerland

    NASA Astrophysics Data System (ADS)

    Panziera, Luca; Gabella, Marco; Zanini, Stefano; Hering, Alessandro; Germann, Urs; Berne, Alexis

    2016-06-01

    This paper presents a regional extreme rainfall analysis based on 10 years of radar data for the 159 regions adopted for official natural hazard warnings in Switzerland. Moreover, a nowcasting tool aimed at issuing heavy precipitation regional alerts is introduced. The two topics are closely related, since the extreme rainfall analysis provides the thresholds used by the nowcasting system for the alerts. Warm and cold seasons' monthly maxima of several statistical quantities describing regional rainfall are fitted to a generalized extreme value distribution in order to derive the precipitation amounts corresponding to sub-annual return periods for durations of 1, 3, 6, 12, 24 and 48 h. It is shown that regional return levels exhibit a large spatial variability in Switzerland, and that their spatial distribution strongly depends on the duration of the aggregation period: for accumulations of 3 h and shorter, the largest return levels are found over the northerly alpine slopes, whereas for longer durations the southern Alps exhibit the largest values. The inner alpine chain shows the lowest values, in agreement with previous rainfall climatologies. The nowcasting system presented here is aimed to issue heavy rainfall alerts for a large variety of end users, who are interested in different precipitation characteristics and regions, such as, for example, small urban areas, remote alpine catchments or administrative districts. The alerts are issued not only if the rainfall measured in the immediate past or forecast in the near future exceeds some predefined thresholds but also as soon as the sum of past and forecast precipitation is larger than threshold values. This precipitation total, in fact, has primary importance in applications for which antecedent rainfall is as important as predicted one, such as urban floods early warning systems. The rainfall fields, the statistical quantity representing regional rainfall and the frequency of alerts issued in case of

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

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

    As part of the African Monsoon Multidisciplinary Analysis (AMMA) field campaign an X-band dual-polarization Doppler radar was deployed in Benin, West-Africa, in 2006 and 2007, together with a reinforced rain gauge network and several optical disdrometers. Based on this data set, a comparative study of several rainfall estimators that use X-band polarimetric radar data is presented. In tropical convective systems as encountered in Benin, microwave attenuation by rain is significant and quantitative precipitation estimation (QPE) at X-band is a challenge. Here, several algorithms based on the combined use of reflectivity, differential reflectivity and differential phase shift are evaluated against rain gauges and disdrometers. Four rainfall estimators were tested on twelve rainy events: the use of attenuation corrected reflectivity only (estimator R(ZH)), the use of the specific phase shift only R(KDP), the combination of specific phase shift and differential reflectivity R(KDP,ZDR) and an estimator that uses three radar parameters R(ZH,ZDR,KDP). The coefficients of the power law relationships between rain rate and radar variables were adjusted either based on disdrometer data and simulation, or on radar-gauges observations. The three polarimetric based algorithms with coefficients predetermined on observations outperform the R(ZH) estimator for rain rates above 10 mm/h which explain most of the rainfall in the studied region. For the highest rain rates (above 30 mm/h) R(KDP) shows even better scores, and given its performances and its simplicity of implementation, is recommended. The radar based retrieval of two parameters of the rain drop size distribution, the normalized intercept parameter NW and the volumetric median diameter Dm was evaluated on four rainy days thanks to disdrometers. The frequency distributions of the two parameters retrieved by the radar are very close to those observed with the disdrometer. NW retrieval based on a combination of ZH

  15. 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.

  16. Contribution of long-term accounting for raindrop size distribution variations on quantitative precipitation estimation by weather radar: Disdrometers vs parameter optimization

    NASA Astrophysics Data System (ADS)

    Hazenberg, P.; Uijlenhoet, R.; Leijnse, H.

    2015-12-01

    Volumetric weather radars provide information on the characteristics of precipitation at high spatial and temporal resolution. Unfortunately, rainfall measurements by radar are affected by multiple error sources, which can be subdivided into two main groups: 1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, vertical profile of reflectivity, attenuation, etc.), and 2) errors related to the conversion of the observed reflectivity (Z) values into rainfall intensity (R) and specific attenuation (k). Until the recent wide-scale implementation of dual-polarimetric radar, this second group of errors received relatively little attention, focusing predominantly on precipitation type-dependent Z-R and Z-k relations. The current work accounts for the impact of variations of the drop size distribution (DSD) on the radar QPE performance. We propose to link the parameters of the Z-R and Z-k relations directly to those of the normalized gamma DSD. The benefit of this procedure is that it reduces the number of unknown parameters. In this work, the DSD parameters are obtained using 1) surface observations from a Parsivel and Thies LPM disdrometer, and 2) a Monte Carlo optimization procedure using surface rain gauge observations. The impact of both approaches for a given precipitation type is assessed for 45 days of summertime precipitation observed within The Netherlands. Accounting for DSD variations using disdrometer observations leads to an improved radar QPE product as compared to applying climatological Z-R and Z-k relations. However, overall precipitation intensities are still underestimated. This underestimation is expected to result from unaccounted errors (e.g. transmitter calibration, erroneous identification of precipitation as clutter, overshooting and small-scale variability). In case the DSD parameters are optimized, the performance of the radar is further improved, resulting in the best performance of the radar QPE product. However

  17. 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

  18. 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.

  19. 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.

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

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  1. 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

    2016-07-01

    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

  2. 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.

  3. 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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2011-06-01

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

  6. Performance evaluation of high-resolution rainfall estimation by X-band dual-polarization radar for flash flood applications in mountainous basins

    NASA Astrophysics Data System (ADS)

    Anagnostou, Marios N.; Kalogiros, John; Anagnostou, Emmanouil N.; Tarolli, Michele; Papadopoulos, Anastasios; Borga, Marco

    2010-11-01

    SummaryDifferent relations between surface rainfall rate, R, and high-resolution polarimetric X-band radar observations were evaluated using a dense network of rain gauge measurements over complex terrain in Central Italian Alps. The specific differential phase shift, KDP, rainfall algorithm (RKDP) although associated with low systematic error it exhibits low sensitivity to the spatial variability of rainfall as compared to the standard algorithm (RSTD) that is based on the reflectivity-to-rainfall (Z-R) relationship. On the other hand, the dependence of the reflectivity measurement on the absolute radar calibration and the rain-path radar signal attenuation introduces significant systematic error on the RSTD rainfall estimates. The study shows that adjusting the Z-R relationship for mean-field bias determined using the RKDP estimates as reference is the best technique for acquiring unbiased radar-rainfall estimates at fine space-time scales. Overall, the bias of the RKDP-adjusted Z-R estimator is shown to be lower than 10% for both storm cases, while the relative root-mean-square error is shown to range from 0.6 (convective storm) to 0.9 (stratiform storm). A vertical rainfall profile correction (VPR) technique is tested in this study for the stratiform storm case. The method is based on a newly developed VPR algorithm that uses the X-band polarimetric information to identify the properties of the melting layer and devices a precipitation profile that varies for each radar volume scan to correct the radar-rainfall estimates. Overall, when accounting for the VPR effect there is up to 70% reduction in the systematic error of the 3° elevation estimates, while the reduction in terms of relative root-mean-square error is limited to within 10%.

  7. 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.

  8. 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.

  9. 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

  10. A grid-based distributed flood forecasting model for use with weather radar data: Part 1. Formulation

    NASA Astrophysics Data System (ADS)

    Bell, V. A.; Moore, R. J.

    A practical methodology for distributed rainfall-runoff modelling using grid square weather radar data is developed for use in real-time flood forecasting. The model, called the Grid Model, is configured so as to share the same grid as used by the weather radar, thereby exploiting the distributed rainfall estimates to the full. Each grid square in the catchment is conceptualised as a storage which receives water as precipitation and generates water by overflow and drainage. This water is routed across the catchment using isochrone pathways. These are derived from a digital terrain model assuming two fixed velocities of travel for land and river pathways which are regarded as model parameters to be optimised. Translation of water between isochrones is achieved using a discrete kinematic routing procedure, parameterised through a single dimensionless wave speed parameter, which advects the water and incorporates diffusion effects through the discrete space-time formulation. The basic model routes overflow and drainage separately through a parallel system of kinematic routing reaches, characterised by different wave speeds but using the same isochrone-based space discretisation; these represent fast and slow pathways to the basin outlet, respectively. A variant allows the slow pathway to have separate isochrones calculated using Darcy velocities controlled by the hydraulic gradient as estimated by the local gradient of the terrain. Runoff production within a grid square is controlled by its absorption capacity which is parameterised through a simple linkage function to the mean gradient in the square, as calculated from digital terrain data. This allows absorption capacity to be specified differently for every grid square in the catchment through the use of only two regional parameters and a DTM measurement of mean gradient for each square. An extension of this basic idea to consider the distribution of gradient within the square leads analytically to a Pareto

  11. A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeastern USA.

    PubMed

    Farnsworth, Andrew; Van DOREN, Benjamin M; Hochachka, Wesley M; Sheldon, Daniel; Winner, Kevin; Irvine, Jed; Geevarghese, Jeffrey; Kelling, Steve

    2016-04-01

    Billions of birds migrate at night over North America each year. However, few studies have described the phenology of these movements, such as magnitudes, directions, and speeds, for more than one migration season and at regional scales. In this study, we characterize density, direction, and speed of nocturnally migrating birds using data from 13 weather surveillance radars in the autumns of 2010 and 2011 in the northeastern USA. After screening radar data to remove precipitation, we applied a recently developed algorithm for characterizing velocity profiles with previously developed methods to document bird migration. Many hourly radar scans contained windborne "contamination," and these scans also exhibited generally low overall reflectivities. Hourly scans dominated by birds showed nightly and seasonal patterns that differed markedly from those of low reflectivity scans. Bird migration occurred during many nights, but a smaller number of nights with large movements of birds defined regional nocturnal migration. Densities varied by date, time, and location but peaked in the second and third deciles of night during the autumn period when the most birds were migrating. Migration track (the direction to which birds moved) shifted within nights from south-southwesterly to southwesterly during the seasonal migration peaks; this shift was not consistent with a similar shift in wind direction. Migration speeds varied within nights, although not closely with wind speed. Airspeeds increased during the night; groundspeeds were highest between the second and third deciles of night, when the greatest density of birds was migrating. Airspeeds and groundspeeds increased during the fall season, although groundspeeds fluctuated considerably with prevailing winds. Significant positive correlations characterized relationships among bird densities at southern coastal radar stations and northern inland radar stations. The quantitative descriptions of broadscale nocturnal migration

  12. A characterization of autumn nocturnal migration detected by weather surveillance radars in the northeastern USA.

    PubMed

    Farnsworth, Andrew; Van DOREN, Benjamin M; Hochachka, Wesley M; Sheldon, Daniel; Winner, Kevin; Irvine, Jed; Geevarghese, Jeffrey; Kelling, Steve

    2016-04-01

    Billions of birds migrate at night over North America each year. However, few studies have described the phenology of these movements, such as magnitudes, directions, and speeds, for more than one migration season and at regional scales. In this study, we characterize density, direction, and speed of nocturnally migrating birds using data from 13 weather surveillance radars in the autumns of 2010 and 2011 in the northeastern USA. After screening radar data to remove precipitation, we applied a recently developed algorithm for characterizing velocity profiles with previously developed methods to document bird migration. Many hourly radar scans contained windborne "contamination," and these scans also exhibited generally low overall reflectivities. Hourly scans dominated by birds showed nightly and seasonal patterns that differed markedly from those of low reflectivity scans. Bird migration occurred during many nights, but a smaller number of nights with large movements of birds defined regional nocturnal migration. Densities varied by date, time, and location but peaked in the second and third deciles of night during the autumn period when the most birds were migrating. Migration track (the direction to which birds moved) shifted within nights from south-southwesterly to southwesterly during the seasonal migration peaks; this shift was not consistent with a similar shift in wind direction. Migration speeds varied within nights, although not closely with wind speed. Airspeeds increased during the night; groundspeeds were highest between the second and third deciles of night, when the greatest density of birds was migrating. Airspeeds and groundspeeds increased during the fall season, although groundspeeds fluctuated considerably with prevailing winds. Significant positive correlations characterized relationships among bird densities at southern coastal radar stations and northern inland radar stations. The quantitative descriptions of broadscale nocturnal migration

  13. 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.

  14. 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…

  15. 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

  16. 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

  17. 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

  18. Comparison of TRMM precipitation radar and microwave imager rainfall retrievals in tropical cyclone inner cores and rainbands

    NASA Astrophysics Data System (ADS)

    Zagrodnik, Joseph P.; Jiang, Haiyan

    2013-01-01

    Tropical Rainfall Measuring Mission (TRMM) rainfall retrieval algorithms are evaluated in tropical cyclone (TC) inner cores (IC), inner bands (IB), and outer rainbands (OB). In total, 1329 IC, 2149 IB, and 4627 OB storm regions are analyzed using data from a 12-year TRMM Tropical Cyclone Precipitation Feature (TCPF) database containing 1013 TCs viewed from December 1997 to December 2009. Attention is focused on the difference between the Precipitation Radar (PR) 2A25 and the TRMM Microwave Imager (TMI) 2A12 rainfall algorithms. The PR 2A25 produces larger mean rain rates than the TMI 2A12 in inner cores and inner bands, with the greatest difference occurring in hurricanes. This discrepancy is caused mostly by the TMI 2A12 significantly underestimating regions of moderate to heavy rain >15 mm hour-1 or when the PR reflectivity is greater than 30 dBZ. The TMI 2A12 rain rates are most closely related to the percentage coverage of 85 GHz polarization-corrected brightness temperature (PCT) <225 K in the IC and 85 GHz PCT <250 K in the IB and OB. These convective parameters are good predictors of the mean TMI 2A12 rain rate, but significant ice scattering is not always present in areas of heavy rain that are often widespread in TC inner regions. As a result, the TMI 2A12 algorithm may poorly measure the rain rate, particularly in the inner core of hurricanes.

  19. Stability of the U.S. weather radar network and its implications for TRMM and GPM ground validation

    NASA Astrophysics Data System (ADS)

    Morris, K. R.; Schwaller, M.; Marks, D. A.; Wolff, D. B.; Petersen, W. A.; Pippitt, J. L.

    2013-12-01

    Ground validation of rainfall and reflectivity measurements from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite has relied on comparisons to measurements from ground radars (GR), in particular to those from the WSR-88D radar network over the U.S. In support of TRMM PR validation and in preparation for validation of the Dual-frequency Precipitation Radar for the upcoming Global Precipitation Measurement (GPM) mission, NASA established a Validation Network (VN) of 21 WSR-88D sites in the southeastern U.S. Quality-controlled data from these sites have been used to perform reflectivity and rain rate comparisons to TRMM PR continually since mid-2006. VN data were used to assess the stability and calibration accuracy of the WSR-88D radars. The PR-GR reflectivity and rain rate comparisons are based on a technique of 3-D volume and resolution matching between the two radar observation systems, where each matching volume is characterized by location, rain type, proximity to the bright band, and quality of the matchup in terms of beam filling and uniformity. Calibration differences between PR and GR are evaluated by inspecting stratiform rain samples above the bright band, where PR attenuation and reflectivity gradient effects are minimal. Time series of GR-PR mean reflectivity differences reveal site-specific trends in GR calibration, under the assumption that the PR calibration is stable and well known. Recent changes in the baseline calibration differences between PR and GR have occurred coincident with upgrades to dual-polarization capability at several VN WSR-88D sites. Overall, 16 of the 21 WSR-88D radars in the GPM Validation Network were found to be running measurably 'cooler' following the dual polarization upgrade, when compared to TRMM PR. These changes are evident in the long-term trend of PR-GR reflectivity comparisons, and in specific examples of short-term anomalies in WSR 88D calibration. Additional, independent

  20. 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.

  1. 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

  2. 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

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

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde

    2016-04-01

    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. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub (https://github.com/overeem11/RAINLINK). The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  4. 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

  5. Wind speed retrieval from Ku-band Tropical Rainfall Mapping Mission precipitation radar data at low incidence angles

    NASA Astrophysics Data System (ADS)

    Ren, Lin; Yang, Jingsong; Zheng, Gang; Wang, Juan

    2016-01-01

    A Ku-band low incidence backscatter model (KuLMOD) for retrieving wind speeds from Tropical Rainfall Mapping Mission (TRMM) precipitation radar (PR) data is proposed. The data set consisted of TRMM PR observations and collocated National Data Buoy Center (NDBC) and Tropical Ocean Global Atmosphere program buoy-measured wind and wave data. The TRMM PR data properties were analyzed with regard to their dependence on spatial resolution, wind speed, relative wind direction, and significant wave height. The KuLMOD model was developed using incidence angles (0.5 to 6.5 deg) and wind speeds (1.5 to 16.5 m/s) as inputs. The model coefficients were derived by fitting the collocated data. The KuLMOD-derived normalized radar cross section, σ0, was compared with those obtained from the TRMM PR observations and a quasi-specular theoretical model and showed good agreement. With the KuLMOD, the wind speeds were retrieved from the TRMM PR data using the least squares method and validated with the buoy measurements, yielding a root mean square error of 1.45 m/s. The retrieval accuracies for the different incidence angles, wind speeds, and spatial resolutions were obtained.

  6. 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...

  7. 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...

  8. Remote rainfall sensing for landslide hazard analysis

    USGS Publications Warehouse

    Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay

    2001-01-01

    Methods of assessing landslide hazards and providing warnings are becoming more advanced as remote sensing of rainfall provides more detailed temporal and spatial data on rainfall distribution. Two recent landslide disasters are examined noting the potential for using remotely sensed rainfall data for landslide hazard analysis. For the June 27, 1995, storm in Madison County, Virginia, USA, National Weather Service WSR-88D Doppler radar provided rainfall estimates based on a relation between cloud reflectivity and moisture content on a 1 sq. km. resolution every 6 minutes. Ground-based measurements of rainfall intensity and precipitation total, in addition to landslide timing and distribution, were compared with the radar-derived rainfall data. For the December 14-16, 1999, storm in Vargas State, Venezuela, infrared sensing from the GOES-8 satellite of cloud top temperatures provided the basis for NOAA/NESDIS rainfall estimates on a 16 sq. km. resolution every 30 minutes. These rainfall estimates were also compared with ground-based measurements of rainfall and landslide distribution. In both examples, the remotely sensed data either overestimated or underestimated ground-based values by up to a factor of 2. The factors that influenced the accuracy of rainfall data include spatial registration and map projection, as well as prevailing wind direction, cloud orientation, and topography.

  9. 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

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

    PubMed

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

    2013-06-01

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

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

    NASA Technical Reports Server (NTRS)

    Nicholson, Shaun R.

    1994-01-01

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

  12. Simulation of Nor'westers using Doppler weather radar wind observations in a mesoscale model

    NASA Astrophysics Data System (ADS)

    Das, Someshwar; Abhilash, S.; Das Gupta, Munmun

    2006-12-01

    Severe thunderstorms form over the Eastern and Northeastern parts of India, i.e., Gangetic West Bengal, Jharkhand, Orissa, Assam and parts of Bihar during the pre-monsoon months (April-May). These storms are known as "Nor'wester" as they move from Northwest to Southeast. In this study we have made numerical simulations of 10 thunderstorms that formed over the West Bengal region during April-May of 2005 and 2006. Numerical simulations have been carried out using MM5 mesoscale model (at 10 km resolution) using conventional and non-conventional observations from Doppler Weather Radar (DWR) and satellites. Composite characteristics of the Nor'wester have been made based upon the simulations. Results indicate that the Nor'westers occur generally when the CAPE increases above 1500 J Kg -1. They have updraft speeds up to 3-4 m s -1, while the downdrafts have magnitudes of about 0.4 - 0.5 m s -1. The updrafts can extend up to 8-9 km altitudes. The total amount of hydrometeors simulated inside the Nor'westers is up to 600-800 mg kg -1. Large amount of ice and snow exist at upper levels, while liquid water is present in the lower levels. The magnitudes of the ice, snow and liquid water depend on the stage of their life cycle.

  13. 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.

  14. Use of X-band weather radar to support the terrain database integrity monitoring and terrain referenced navigation function

    NASA Astrophysics Data System (ADS)

    Singh, Abhijeet; Uijt de Haag, Maarten

    2007-04-01

    To enable safe use of Synthetic Vision Systems (SVS) at lower altitudes, real-time sensor measurements are required to ensure the integrity of terrain and obstacle models stored in the onboard SVS and to detect hazards that may have been omitted from the stored models. This paper discusses various aspects of using X-band weather radar for terrain database integrity monitoring and terrain referenced navigation. Feature extraction methods will be addressed to support the correlation process between the weather radar measurements and the stored terrain databases. Furthermore, improved weather radar antenna models will be discussed to more reliably perform the shadow detection and extraction (SHADE) functionality. In support of the navigation function, methods will be introduced to estimate aircraft state information, such as velocity, from the geometrical changes in the observed terrain imagery. The outputs of these methods will be compared to the state estimates derived from Global Positioning System (GPS) and Inertial Navigation System (INS) measurements. All methods discussed in this paper will be evaluated using flight test data collected with a Gulfstream V in Reno, NV.

  15. 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

  16. Correcting the radar rainfall forcing of a hydrologic model with data assimilation: application to flood forecasting in the Lez Catchment in Southern France

    NASA Astrophysics Data System (ADS)

    Harader, E. B.; Estupina-Borrell, V.; Ricci, S. M.; Coustau, M.; Thual, O.; Bouvier, C.

    2011-12-01

    For flood prediction and watershed characterization, radar data can provide a key advantage in terms of temporal and spatial resolution, as runoff generation is sensitive to rainfall location. However, the radar data input to the hydrological model is subject to uncertainties related to a non-linear vertical reflectivity profile (Borga, 2002), calibration of the Z-R relationship and beam blocking effects (Vieux & Bedient, 2004). Specifically for the Lez catchment, radar data quality varies on a seasonal basis and is degraded in winter (Coustau et al., 2011). These uncertainties translate to errors in the simulated discharges. Data assimilation techniques can be applied to improve the quality of radar data or parameters input to the hydrological model. Rainfall inputs were corrected by a factor of α, calculated separately for each event by assimilating observed discharges. This coefficient was compared with the mean field bias (MFB), a corrective coefficient determined using ground rainfall measurements (Vieux & Bedient, 2004). Simulations were then performed in the context of 'real-time' peak discharge prediction and corrected using data assimilation. A set of 18 rainfall events was used to simulate discharges for the 114 km2 Lez Catchment, which is subject to heavy orographic rainfall and characterized by a karstic geology. A distributed, event-based, parsimonious hydrological model was used, with runoff production controlled by a modified SCS method, parameterized by S, representing the initial soil moisture deficit (Coustau et al., 2011). Application of the data assimilation algorithm was carried out in two different modes: re-analysis, in which all observations during the flood event are assimilated and prevision, in which only observations before the event peak are assimilated. In re-analysis mode, the soil moisture content was initialized by an S calibrated for the simulation forced by MFB corrected rainfall. In prevision mode, the soil moisture deficit was

  17. 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.

  18. Dual polarisation C-band weather radar imagery of the 6 August 2012 Te Maari Eruption, Mount Tongariro, New Zealand

    NASA Astrophysics Data System (ADS)

    Crouch, John F.; Pardo, Natalia; Miller, Craig A.

    2014-10-01

    The 6 August 2012 eruption of Mt. Tongariro from Upper Te Maari Crater in the central North Island of New Zealand was the first volcanic eruption observed by an operational weather radar in New Zealand, and is believed to be one of only a small number of eruptions observed by a dual-polarisation radar worldwide. The eruption was also observed by a GeoNet webcam, and detailed ash deposit studies have permitted analysis of the plume characteristics. A combination of radar and webcam imagery show 5 pulses within the first 13 min of the eruption, and also the subsequent ash transport downwind. Comparison with ash samples show the radar was likely detecting ash particles down to about 0.5 mm diameter. The maximum plume height estimated by the radar is 7.8 ± 1.0 km above mean sea level (amsl), although it is possible this may be a slight under estimation if very small ash particles not detected by the radar rose higher and comprised the very top of the plume. The correlation coefficient and differential reflectivity fields that are additionally measured by the dual polarisation radar provide extra information about the structure and composition of the eruption column and ash cloud. The correlation coefficient easily discriminates between the eruption column and the ash plume, and provides some information about the diversity of ash particle size within both the ash plume and the subsequent detached ash cloud drifting downwind. The differential reflectivity shows that the larger ash particles are falling with a horizontal orientation, and indicates that ice nucleation and aggregation of fine ash particles was probably occurring at high altitudes within 20-25 min of the eruption.

  19. Rainfall Process Partitioning Using S-PROF Radar Observations Collected During the CalWater Field Campaign Winters

    NASA Astrophysics Data System (ADS)

    White, A. B.; Neiman, P. J.; Creamean, J.; Hughes, M. R.; Moore, B.; Ralph, F. M.; Prather, K. A.

    2011-12-01

    Vertically pointing S-band radar (S-PROF) observations collected during the CalWater field campaign winter wet seasons are analyzed to partition the observed rainfall into three primary categories: brightband (BB) rain, non-brightband (NBB) rain, and convective rain. NBB rain is primarily a shallow, warm rain process driven by collision and coalescence. Because of its shallow nature, NBB rain is often undetected by the operational NEXRAD radar network. Previous rainfall process partitioning analysis conducted for a coastal mountain site in California has shown that NBB rain contributes about one-third, on average, of the total wet season precipitation observed there. Shallow moist flow with near neutral stability, which is often present in the coastal environment during the warm sectors of landfalling storms, is a key ingredient in the formation of NBB rain. However, NBB rain also has been observed in other storm regimes (e.g., post-cold frontal). NBB rain has been shown to produce rain rates known by forecasters to be capable of producing floods. During the CalWater field campaign winters, S-PROF radars were located in the Sierra Nevada at Sugar Pine Dam (SPD) for three consecutive winters (2009-2011) and at Mariposa (MPI) for the latter two winters (2010-2011). During the southwesterly flow present in the warm sectors of many California landfalling storms, the SPD site was directly downwind of the gap in coastal terrain associated with the San Francisco Bay Delta. This orientation would allow relatively unmodified maritime flow to arrive at SPD. The MPI site was located further south such that airflow arriving at this site during winter storms likely was processed by the coastal terrain south of San Francisco Bay. In this presentation we will examine whether the relative locations of SPD and MPI relative to the coastal terrain impacted the amount of NBB rain that was observed at each site during the CalWater wet seasons. We will use synoptic and mesoscale

  20. Whirl Wind Detection and Identification in Indonesia Utilizing Single Polarization Doppler Weather Radar Volumetric Data

    NASA Astrophysics Data System (ADS)

    Ali, Abdullah; Hidayati, Sabitul

    2016-06-01

    Whirl wind occurrence frequency in Indonesia tends increasing in the last five years. Geospatial data from National Agency for Disaster Management (BNPB) recorded 72 cases with the impact of the two victims died, ten injured, 485 people were evacuated, and 1285 buildings were destroyed at period of January-June 2015. Based on the impact, early warning through remote sensing by using single polarization Doppler weather radar is need to be efforted. Whirl wind detection is done by identifying the characteristic pattern of the rotating convective cloud system by hook echo, analyzing the exsistance of vortex and rotation, and the strength of turbulence. The results show horizontal wind profile with a rotational pattern at CAPPI (V) and HWIND (V) by the altitude of 0.5 km, strong turbulence through product CAPPI (W) 0.5 km ranged of 1.75-2.05 ms-1, the vertical wind profile by product VVP (V) with a maximum value updraft reaches more than 20 knots at a 100-200 meters height, strong horizontal wind shear through HSHEAR (V) and CAPPI (HSHEAR) altitude of 0.5 km with a range of 6.23 to 10.12 ms-1/km. SWI and SSA show that the cloud base height is very low ranged from 200-600 meters with a maximum reflectivity reached 61.5 dBZ by top cloud height reached 14 km, while the product CAPPI (Z) 0.5 km and CMAX (Z) is very difficult to identify patterns hook echo. The results of remote sensing are very representative with the physical properties of whirl wind even whirl wind in a smaller scale.

  1. 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

  2. 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

  3. 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

  4. Rain-Mapping Radar

    NASA Technical Reports Server (NTRS)

    Im, K. E.; Li, F. K.; Wilson, W. J.; Rosing, D.

    1988-01-01

    Orbiting radar system measures rates of rainfall from 0.5 to 60 mm/h. Radar waves scattered and absorbed by rainfall to extents depending on wavelength, polarization, rate of rainfall, and distribution of sizes and shapes of raindrops. Backscattered radar signal as function of length of path through rain used to infer detailed information about rain. Accumulated radar return signals processed into global maps of monthly average rainfall for use in climatological studies.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. High-Resolution Rainfall From Radar Reflectivity and Terrestrial Rain Gages for use in Estimating Debris-Flow Susceptibility in the Day Fire, California

    NASA Astrophysics Data System (ADS)

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

    2007-12-01

    Constraining the distribution of rainfall is essential to evaluating the post-fire mass-wasting response of steep soil-mantled landscapes. As part of a pilot early-warning project for flash floods and debris flows, NOAA deployed a portable truck-mounted Shared Mobile Atmospheric Research and Teaching Radar (SMART-R) to the 2006 Day fire in the Transverse Ranges of Southern California. In conjunction with a dense array of ground- based instruments, including 8 tipping-bucket rain gages located within an area of 170 km2, this C-band mobile Doppler radar provided 200-m grid cell estimates of precipitation data at fine temporal and spatial scales in burned steeplands at risk from hazardous flash floods and debris flows. To assess the utility of using this data in process models for flood and debris flow initiation, we converted grids of radar reflectivity to hourly time-steps of precipitation using an empirical relationship for convective storms, sampling the radar data at the locations of each rain gage as determined by GPS. The SMART-R was located 14 km from the farthest rain gage, but <10 km away from our intensive research area, where 5 gages are located within <1-2 km of each other. Analyses of the nine storms imaged by radar throughout the 2006/2007 winter produced similar cumulative rainfall totals between the gages and their SMART-R grid location over the entire season which correlate well on the high side, with gages recording the most precipitation agreeing to within 11% of the SMART-R. In contrast, on the low rainfall side, totals between the two recording systems are more variable, with a 62% variance between the minimums. In addition, at the scale of individual storms, a correlation between ground-based rainfall measurements and radar-based rainfall estimates is less evident, with storm totals between the gages and the SMART-R varying between 7 and 88%, a possible result of these being relatively small, fast-moving storms in an unusually dry winter. The

  11. Polarimetric X-band weather radar measurements in the tropics: radome and rain attenuation correction

    NASA Astrophysics Data System (ADS)

    Schneebeli, M.; Sakuragi, J.; Biscaro, T.; Angelis, C. F.; Carvalho da Costa, I.; Morales, C.; Baldini, L.; Machado, L. A. T.

    2012-09-01

    A polarimetric X-band radar has been deployed during one month (April 2011) for a field campaign in Fortaleza, Brazil, together with three additional laser disdrometers. The disdrometers are capable of measuring the raindrop size distributions (DSDs), hence making it possible to forward-model theoretical polarimetric X-band radar observables at the point where the instruments are located. This set-up allows to thoroughly test the accuracy of the X-band radar measurements as well as the algorithms that are used to correct the radar data for radome and rain attenuation. For the campaign in Fortaleza it was found that radome attenuation dominantly affects the measurements. With an algorithm that is based on the self-consistency of the polarimetric observables, the radome induced reflectivity offset was estimated. Offset corrected measurements were then further corrected for rain attenuation with two different schemes. The performance of the post-processing steps was analyzed by comparing the data with disdrometer-inferred polarimetric variables that were measured at a distance of 20 km from the radar. Radome attenuation reached values up to 14 dB which was found to be consistent with an empirical radome attenuation vs. rain intensity relation that was previously developed for the same radar type. In contrast to previous work, our results suggest that radome attenuation should be estimated individually for every view direction of the radar in order to obtain homogenous reflectivity fields.

  12. 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.

  13. 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

  14. 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.

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

    NASA Astrophysics Data System (ADS)

    Cloppet, E.; Regimbeau, M.

    2009-09-01

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

  16. 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.

  17. An investigation of a new dual-polarization weather radar data model for lightning nowcasting and warning

    NASA Astrophysics Data System (ADS)

    Ruzanski, Evan; Chandrasekar, Venkatachalam

    2016-04-01

    Accurate and extended short-term automated forecasting (nowcasting) of lightning is important for the preservation of life and resources in many applications. A new dual-polarization weather radar data model for lightning nowcasting and warning is presented and described. Previous research has shown that a simplified radar-based ice mass estimator provides value in lightning nowcasting and warning. This new product estimates the mass of graupel aloft, a quantity shown to be a key component in the atmospheric electrification process. The mass of graupel in the charge region of the storm is estimated by a model comprised of integrated reflectivity above the environmental freezing level, classification of graupel regions by a new hydrometeor classification algorithm, and coefficients determined by bulk microphysics studies. Data from storm events collected by the KFWS WSR-88D and National Lightning Detection Network in the Dallas-Fort Worth urban area in 2014 are used for analysis. Nowcasting is done using an area-based approach called the Dynamic and Adaptive Radar Tracking of Storms, where storm motion is estimated using a Fourier-based linear model. Nowcasts are then generated by advecting the data fields ahead in time according to these estimated motion vectors. Warning verification in the 0-1 h lead time frame is performed using a grid-based approach that discerns the performance of first-lightning flash nowcasting at each grid point.

  18. 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

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

    NASA Technical Reports Server (NTRS)

    Meneghini, R.; Liao, L.

    2007-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Accurate rainfall observations with high spatial and temporal resolutions are needed for many applications, for instance, as input for hydrological models. Weather radars often provide data with sufficient spatial and temporal resolution, but usually need adjustment. In general, only few rain gauge measurements are available to adjust the radar data in real-time, for example, each hour. Physically based methods, such as a VPR correction, can be valuable and hold a promise. However, they are not always performed in real-time yet and can be difficult to implement. The estimation of rainfall using microwave links from commercial cellular telephone networks is a new and potentially valuable source of information. Such networks cover large parts of the land surface of the earth and have a high density. The data produced by the microwave links in such networks is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A recent study of us shows that urban rainfall can be estimated from commercial microwave link data for the Rotterdam region, a densely-populated delta city in the Netherlands. A data set from a commercial microwave link network over the Netherlands is analyzed, containing approximately 1500 links covering the land surface of the Netherlands (35500 km2). This data set consists of several days with extreme rainfall in June, July and August 2011. A methodology is presented to derive rainfall intensities and daily rainfall depths from the microwave link data, which have a temporal resolution of 15 min. The magnitude and dynamics of these rainfall intensities

  1. A seamless flash-flood early warning tool based on IDF-curves and coupling of weather-radar with numerical weather predictions

    NASA Astrophysics Data System (ADS)

    Liechti, Kaethi; Knechtl, Valentin; Andres, Norina; Sideris, Ioannis; Zappa, Massimiliano

    2014-05-01

    A flash-flood is a flood that develops rapidly after a heavy precipitation event. Flash-flood forecasting is an important field of research because flash floods cause a lot of fatalities and damage. A flash-flood early warning tool is developed based on precipitation statistics. Our target areas are small ungauged areas of southern-Switzerland. A total of 759 sub-cathcments was considered. In a first intensity-duration-frequency (IDF) curves for each catchment have been calculated basin on: A) Gridded precipitation products for the period 1961 to 2012 and B) gridded reforecast of the COSMO-LEPS NWP for the period 1971-2000. These different IDF-curves at the catchment level in combination with precipitation forecasts are the basis for the flash-flood early warning tool. The forecast models used are COSMO-2 (deterministic, updated every three hours and with a lead time of 24 hours) and COSMO-LEPS (probabilistic, 16 member and with a lead time of five days). In operational mode COSMO-2 is nudged to real-time data of a weather-radar precipitation obtained by blending the radar qpe with information from a national network of precipitation data. This product is called COMBIPRECIP. The flash-flood early warning tool has been evaluated against observed events. These events are either discharge peaks in gauged sub-areas or reports of damages caused by flash-flood events. The hypothesis that it is possible to detect hydrological events with the flash-flood early warning tool can be partly confirmed. The highest skill is obtained if the return-period of weather radar QPE is assessed at hourly time scale. With this it was possible to confirm most of the damage events occurred in 2010 and 2011. The prototype tool is affected by several false alarms. This is because initial conditions of the soils are not considered. Further steps will be therefore focussed on the addition of real-time hydrological information as obtained from the application of high resolution distributed

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. Combining and comparing weather radar measurements and rain gauge measurements of precipitation in a fruit growing area

    NASA Astrophysics Data System (ADS)

    Sivertsen, T. H.; Rafoss, T.

    2003-04-01

    A small fruit growing area of southern Norway is chosen as a pilot area. This area contains four automated meteorological stations owned by The Norwegian Crop Research Institute. The measurements made at the stations are hourly recordings of precipitation, air temperature, leaf wetness and relative humidity of the air, plus some additional measurements at some stations. The area has a relatively smooth topography with hills and no mountains. The highest point is located about 300 m above the sea level, and the lowest 15 m above sea level. The remote sensing research group at The Norwegian Meteorological Institute is providing the hourly radar measurements of precipitation, from two different weather radars. All the precipitation data used is documented according to a system developed by The Norwegian Crop Research Institute, and for the growing season ahead data will be distributed to the local private extension service, but this year there will be no development of biological models serving the fruit growers (apple scab etc) using all the additional relevant data. The outcome of the use of the operational use of the data in the coming growing season, will be comparing the data from the different sources, and looking closer at the possible significance of the use of a documentation system for the data from different sources. Finally the quality of the data is discussed, as well as the possible steps to be taken for future and extended use of such data.

  8. 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.

  9. 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.

  10. 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.

  11. Using X-band weather radar measurements to monitor the integrity of digital elevation models for synthetic vision systems

    NASA Astrophysics Data System (ADS)

    Young, Steven D.; Uijt de Haag, Maarten; Sayre, Jonathon

    2003-09-01

    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. Futher, 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 real-time 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 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.

  12. 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

  13. 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.

  14. Landslide occurrences and recurrence intervals of heavy rainfalls in Japan

    NASA Astrophysics Data System (ADS)

    Saito, H.; Uchida, T.; Matsuyama, H.; Korup, O.

    2015-12-01

    Dealing with predicted increases in extreme weather conditions due to climate change requires robust knowledge about controls on rainfall-triggered landslides. This study developed the probable rainfall database from weather radar data, and analyzed the potential correlation between the landslide magnitude-frequency and the recurrence interval of the heavy rainfall across Japan. We analyzed 4,744 rainfall-induced landslides (Saito et al., 2014, Geology), 1 to 72 h rainfalls, and soil water index (SWI). We then estimated recurrence intervals for these rainfall parameters using a Gumbel distribution with jackknife fitting. Results showed that the recurrence intervals of rainfall events which caused landslides (<10^3 m^3) were less than 10 yr across Japan. The recurrence intervals increased with increases in landslide volumes. With regard to the landslides larger than 10^5 m^3, recurrence intervals of the rainfall events were more than 100 yr. These results suggest that recurrence intervals of heavy rainfalls are important for assessing regional landslide hazard in Japan.

  15. 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.

  16. Atmosphere-Truth Z-R Rainfall Estimates: A Fresh Approach to an Old Problem

    NASA Astrophysics Data System (ADS)

    Henz, J. F.

    2010-12-01

    Common modeling practice for basin calibration uses rainfall fields developed by the statistical use of surface rain gauge observed data or the direct application of NEXRAD National Weather Service WSR-88D Doppler radar Storm Total Rainfall or 1-hr rainfall estimations. Each of these approaches has significant limitations. Rain gages often lack sufficient spatial coverage to measure true storm intensity or the distribution of rainfall in a basin. The NWS WSR-88D Doppler radar algorithms are constantly being improved but still fail to deliver consistent rainfall estimates. Significant problems are caused by an under-estimation of warm coalescence rains and an over-estimation of rainfall in both dry environments and storms with hail contamination. Finally, storm updraft areas are frequently counted as raining portions of the storm producing immediate errors. The statistical techniques often under-estimate rainfall when the heavy rain core of the storm misses the rain gauges or if high winds cause an under-catchment of rainfall. Gauge-adjusted rainfall estimates are also dependant on the core of the storm being observed by a gauge. Statistical approaches often under-estimate rainfall producing insufficient runoff to drive the observed flooding runoffs. The Atmosphere-Truth ZR (ATZR) technique uses an atmosphere-truthed algorithm to produce highly accurate estimates of surface rainfall from Doppler radar data. This approach relies on using a cloud physics approach to determine the atmosphere’s ability to produce 15-min to hourly rain rates. The atmsopheric rainfall is utilizes surface, boundary layer and cloud layer observations of temperature and moisture from conventional National Weather Service observations. The depth of the thunderstorm updraft region that exceeds 0C is used with the precipitable water index and updraft speeds to provide estimates of 15-min to hourly rainfall rates from radar reflectivity areas in the storm greather than 50 dBZ. Rainfall rates

  17. Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

    NASA Astrophysics Data System (ADS)

    Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

    2015-12-01

    Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

  18. 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%).

  19. Weak Linkage between the Heaviest Rainfall and Tallest Storms

    NASA Astrophysics Data System (ADS)

    Hamada, A.; Takayabu, Y. N.; Liu, C.; Zipser, E. J.

    2015-12-01

    Eleven years measurements from the Precipitation Radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite reveals robust differences in rainfall characteristics between extreme rainfall and convection events, irrespective of region. After accumulating `rainfall events' defined as a set of contiguous rainy pixels of TRMM PR measurements for each 2.5 x 2.5 degree grid cell, three different types of regional extreme rainfall events are defined in each grid cell, using the maximum values of near-surface rainfall rate (NSR) and 40-dBZ echo top height (ETH40) in rainfall events; R-only (H-only) extreme events are defined as rainfall events of which the maximum NSR (ETH40) is within top 0.1% but the ETH40 (NSR) is not; RH extreme events are defined as those of which both the maxima of NSR and ETH40 are within top 0.1%. Only a small fraction of rainfall extreme events are found to be related to convective extremes. The 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. There are robust differences in echo profiles, rainfall characteristics, and local environments between extreme rainfall and convection events, irrespective of region. Extreme rainfall events exhibit lower echo-top height and downward increase of radar reflectivity (Ze) below the freezing level, whereas extreme convection events exhibit more vertically aligned echo structure. The echo and environmental characteristics of extreme rainfall events imply the importance of warm-rain processes in producing extreme rainfall. An important concern regarding the PR measurements in Ku band is significant attenuation by severe hailstorms. We performed a statistical evaluation of the PR measurements using 5-yr measurements obtained during the Baiu season (May-June) using a ground-based C-band radar in Okinawa, Japan, and confirmed that the attenuation

  20. 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.

  1. Inter-Comparison of CHARM Data and WSR-88D Storm Integrated Rainfall

    NASA Technical Reports Server (NTRS)

    Jedlovec, Gary J.; Meyer, Paul J.; Guillory, Anthony R.; Stellman, Keith; Limaye, Ashutosh; Arnold, James E. (Technical Monitor)

    2002-01-01

    A localized precipitation network has been established over a 4000 sq km region of northern Alabama in support of local weather and climate research at the Global Hydrology and Climate Center (GHCC) in Huntsville. This Cooperative Huntsville-Area Rainfall Measurement (CHARM) network is comprised of over 80 volunteers who manually take daily rainfall measurements from 85 sites. The network also incorporates 20 automated gauges that report data at 1-5 minute intervals on a 24 h a day basis. The average spacing of the gauges in the network is about 6 kin, however coverage in some regions benefit from gauges every 1-2 km. The 24 h rainfall totals from the CHARM network have been used to validate Stage III rainfall estimates of daily and storm totals derived from the WSR-88D radars that cover northern Alabama. The Stage III rainfall product is produced by the Lower Mississippi River Forecast Center (LMRFC) in support of their daily forecast operations. The intercomparisons between the local rain gauge and the radar estimates have been useful to understand the accuracy and utility of the Stage III data. Recently, the Stage III and CHARM rainfall measurements have been combined to produce an hourly rainfall dataset at each CHARM observation site. The procedure matches each CHARM site with a time sequence of Stage III radar estimates of precipitation. Hourly stage III rainfall estimates were used to partition the rain gauge values to the time interval over which they occurred. The new hourly rain gauge dataset is validated at selected points where 1-5 minute rainfall measurements have been made. This procedure greatly enhances the utility of the CHARM data for local weather and hydrologic modeling studies. The conference paper will present highlights of the Stage III intercomparison and some examples of the combined radar / rain gauge product demonstrating its accuracy and utility in deriving an hourly rainfall product from the 24 h CHARM totals.

  2. 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.

  3. 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.

  4. A simple simulation approach to generate complex rainfall fields conditioned by elevation: example of the eastern Mediterranean region

    NASA Astrophysics Data System (ADS)

    Oriani, Fabio; Ohana-Levi, Noa; Straubhaar, Julien; Renard, Philippe; Karnieli, Arnon; Mariethoz, Grégoire; Morin, Efrat; Marra, Francesco

    2016-04-01

    Stochastically generating realistic rainfall fields is useful to study the uncertainty related to catchment recharge and its propagation to distributed hydrological models. To this end, it is critical to use weather radar images as training data, being the single most informative source for rainfall spatial heterogeneity. Generating realistic simulations is particularly important in regions like the eastern Mediterranean, where the synoptic conditions can lead to rainfall fields presenting various morphology, anisotropy and non-stationarity. The Direct Sampling (DS) technique [Mariethoz2010] is proposed here as a stochastic generator of spatial daily rainfall fields relying on the simulation of radar imagery. The technique is based on resampling of a training data set (in this case, a stack of radar images) and the generation of similar patterns to the ones found in the data. The strong point of DS, which makes it an attractive simulation approach for rainfall, is its capability to preserve the high-order statistical features present in the training image (e.g., rainfall cell shape, spatial non-stationarity) with minimal parameterization. Moreover, factors influencing rainfall, like elevation, can be used as conditioning variables, without the need of a complex statistical dependence model. A DS setup for radar image simulation is presented and tested for the simulation of daily rainfall fields using a 10-year radar-image record from the central region of Israel. Using a synoptic weather classification to train the model, the algorithm can generate realistic spatial fields for different rainfall types, preserving the variability and the covariance structure of the reference reasonably well. Moreover, the simulation is conditioned using the digital elevation model to preserve the complex relation between rainfall intensity and altitude that is characteristic for this region. [Mariethoz2010] G. Mariethoz, P. Renard, and J. Straubhaar. The direct sampling method to

  5. 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...

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

    NASA Astrophysics Data System (ADS)

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko

    2016-06-01

    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 (≈ 35 500 km2) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language "R") is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  7. 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

  8. 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

  9. The response of the high-latitude ionosphere to the coronal mass ejection event of April 6, 2000: A practical demonstration of space weather nowcasting with the Super Dual Auroral Radar Network HF radars

    NASA Astrophysics Data System (ADS)

    Ruohoniemi, J. M.; Barnes, R. J.; Greenwald, R. A.; Shepherd, S. G.

    2001-12-01

    The ionosphere at high latitudes is the site of important effects in space weather. These include strong electrical currents that may disrupt power systems through induced currents and density irregularities that can degrade HF and satellite communication links. With the impetus provided by the National Space Weather Program, the radars of the Super Dual Auroral Radar Network have been applied to the real-time specification (``nowcasting'') of conditions in the high-latitude ionosphere. A map of the plasma convection in the northern high-latitude ionosphere is continually generated at the Johns Hopkins University Applied Physics Laboratory (JHU/APL) SuperDARN web site using data downloaded in real time from the radars via Internet connections. Other nowcast items include information on the conditions of HF propagation, the spatial extent of auroral effects, and the total cross polar cap potential variation. Time series of various parameters and an animated replay of the last 2 hours of convection patterns are also available for review. By comparing with simultaneous measurements from an upstream satellite, it is possible to infer the effective delay from the detection of changes in the solar wind at the satellite to the arrival of related effects in the high-latitude ionosphere. We discuss the space weather products available from the JHU/APL SuperDARN web site and their uses by simulating a nowcast of the ionosphere on April 6, 2000, during the arrival of a coronal mass ejection (CME) -related shock. The nowcast convection pattern in particular satisfies a critical need for timely, comprehensive information on ionospheric electric fields.

  10. Cloud and Precipitation Radar

    NASA Astrophysics Data System (ADS)

    Hagen, Martin; Höller, Hartmut; Schmidt, Kersten

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  13. 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

  14. Rainfall estimation in the context of post-event flash flood analysis

    NASA Astrophysics Data System (ADS)

    Delrieu, Guy; Boudevillain, Brice; Bouilloud, Ludovic

    2010-05-01

    Due to their spatial coverage and space-time resolution, operational weather radar networks offer unprecedented opportunities for the observation of flash flood generating storms. However, the radar rainfall estimation quality highly depends on the relative locations of the event and the radar(s). A mountainous environment obviously adds to the complexity of the radar quantitative precipitation estimation (QPE). A pragmatic methodology was developed within the EC-funded HYDRATE project to take the best benefit of the existing rainfall observations (radar and raingauge data) for given flash-flood cases: 1) A precise documentation of the radar characteristics (location, parameters, operating protocol, data archives and processing) needs first to be established. The radar(s) detection domain(s) can then be characterized using the "hydrologic visibility" concepts (Pellarin et al. J Hydrometeor 3(5) 539-555 2002). 2) Rather dense raingauge observations (operational, amateur) are usually available at the event time scale while few raingauge time series exist at the hydrologic time steps. Such raingauge datasets need to be critically analysed; a geostatistical approach is proposed for this task. 3) A number of identifications can be implemented prior to the radar data re-processing: a) Special care needs to be paid to (residual) ground clutter which has a dramatic impact of radar QPE. Dry-weather maps and rainfall accumulation maps may help in this task. b) Various sources of power losses such as screening, wet radome, attenuation in rain need to be identified and quantified. It will be shown that mountain returns can be used to quantify attenuation effects at C-band. c) Radar volume data is required to characterize the vertical profile of reflectivity (VPR), eventually conditioned on rain type (convective, widespread). When such data is not available, knowledge of the 0°C isotherm and the scanning protocol may help detecting bright-band contaminations that critically

  15. Rainfall estimation in the context of post-event flash flood analysis

    NASA Astrophysics Data System (ADS)

    Bouilloud, L.; Delrieu, G.; Boudevillain, B.

    2009-04-01

    Due to their spatial coverage and space-time resolution, operational weather radar networks offer unprecedented opportunities for the observation of flash flood generating storms. However, the radar rainfall estimation quality highly depends on the relative locations of the event and the radar(s). A mountainous environment obviously adds to the complexity of the radar quantitative precipitation estimation (QPE). A pragmatic methodology is proposed to take the best benefit of the existing rainfall observations (radar and raingauge data) for given flash-flood cases: 1) A precise documentation of the radar characteristics (location, parameters, operating protocol, data archives and processing) needs first to be established. The radar(s) detection domain(s) can then be characterized using the "hydrologic visibility" concepts (Pellarin et al. J Hydrometeor 3(5) 539-555 2002). 2) Rather dense raingauge observations (operational, amateur) are usually available at the event time scale while few raingauge time series exist at the hydrologic time steps. Such raingauge datasets need to be critically analysed; a geostatistical approach is proposed for this task. 3) A number of identifications can be implemented prior to the radar data re-processing: a) Special care needs to be paid to (residual) ground clutter which has a dramatic impact of radar QPE. Dry-weather maps and rainfall accumulation maps may help in this task. b) Various sources of power losses such as screening, wet radome, attenuation in rain need to be identified and quantified. It will be shown that mountain returns can be used to quantify attenuation effects at C-band. c) Radar volume data is required to characterize the vertical profile of reflectivity (VPR), eventually conditioned on rain type (convective, widespread). When such data is not available, knowledge of the 0°C isotherm and the scanning protocol may help detecting bright-band contaminations that critically affect radar QPE. d) With conventional

  16. Frequency of tropical precipitating clouds as observed by the Tropical Rainfall Measuring Mission Precipitation Radar and ICESat/Geoscience Laser Altimeter System

    NASA Astrophysics Data System (ADS)

    Casey, Sean P. F.; Dessler, Andrew E.; Schumacher, Courtney

    2007-07-01

    Convective clouds in the tropics can be grouped into three categories: shallow clouds with cloud top heights near 2 km above the surface, midlevel congestus clouds with tops near the 0°C level, and deep convective clouds capped by the tropopause. This trimodal distribution is visible in cloud data from the Geoscience Laser Altimeter System (GLAS), carried aboard the Ice, Cloud, and land Elevation Satellite (ICESat), as well as in precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). Fractional areal coverage (FAC) data is calculated at each of the three levels to describe how often optically thick clouds or precipitation are seen at each level. By dividing the FAC of TRMM PR-observed precipitation by the FAC of thick GLAS/ICESat-observed clouds, we derive the fraction of clouds that are precipitating. We find that the tropical mean precipitating cloud fraction is low: 3.7% for shallow clouds, 6.5% for midlevel clouds, and 24.1% for deep clouds.

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

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  18. The new approach of polarimetric attenuation correction for improving radar quantitative precipitation estimation(QPE)

    NASA Astrophysics Data System (ADS)

    Gu, Ji-Young; Suk, Mi-Kyung; Nam, Kyung-Yeub; Ko, Jeong-Seok; Ryzhkov, Alexander

    2016-04-01

    To obtain high-quality radar quantitative precipitation estimation data, reliable radar calibration and efficient attenuation correction are very important. Because microwave radiation at shorter wavelength experiences strong attenuation in precipitation, accounting for this attenuation is the essential work at shorter wavelength radar. In this study, the performance of different attenuation/differential attenuation correction schemes at C band is tested for two strong rain events which occurred in central Oklahoma. And also, a new attenuation correction scheme (combination of self-consistency and hot-spot concept methodology) that separates relative contributions of strong convective cells and the rest of the storm to the path-integrated total and differential attenuation is among the algorithms explored. A quantitative use of weather radar measurement such as rainfall estimation relies on the reliable attenuation correction. We examined the impact of attenuation correction on estimates of rainfall in heavy rain events by using cross-checking with S-band radar measurements which are much less affected by attenuation and compared the storm rain totals obtained from the corrected Z and KDP and rain gages in these cases. This new approach can be utilized at shorter wavelength radars efficiently. Therefore, it is very useful to Weather Radar Center of Korea Meteorological Administration preparing X-band research dual Pol radar network.

  19. 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

  20. Countrywide rainfall maps from a commercial cellular telecommunication network

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  1. 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

  2. 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.

  3. Road Weather and Connected Vehicles

    NASA Astrophysics Data System (ADS)

    Pisano, P.; Boyce, B. C.

    2015-12-01

    On average, there are over 5.8 M vehicle crashes each year of which 23% are weather-related. Weather-related crashes are defined as those crashes that occur in adverse weather or on slick pavement. The vast majority of weather-related crashes happen on wet pavement (74%) and during rainfall (46%). Connected vehicle technologies hold the promise to transform road-weather management by providing improved road weather data in real time with greater temporal and geographic accuracy. This will dramatically expand the amount of data that can be used to assess, forecast, and address the impacts that weather has on roads, vehicles, and travelers. The use of vehicle-based measurements of the road and surrounding atmosphere with other, more traditional weather data sources, and create road and atmospheric hazard products for a variety of users. The broad availability of road weather data from mobile sources will vastly improve the ability to detect and forecast weather and road conditions, and will provide the capability to manage road-weather response on specific roadway links. The RWMP is currently demonstrating how weather, road conditions, and related vehicle data can be used for decision making through an innovative Integrated Mobile Observations project. FHWA is partnering with 3 DOTs (MN, MI, & NV) to pilot these applications. One is a mobile alerts application called the Motorists Advisories and Warnings (MAW) and a maintenance decision support application. These applications blend traditional weather information (e.g., radar, surface stations) with mobile vehicle data (e.g., temperature, brake status, wiper status) to determine current weather conditions. These weather conditions, and other road-travel-relevant information, are provided to users via web and phone applications. The MAW provides nowcasts and short-term forecasts out to 24 hours while the EMDSS application can provide forecasts up to 72 hours in advance. The three DOTs have placed readers and external

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

    NASA Astrophysics Data System (ADS)

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

    2006-08-01

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

  5. Calibration of Local Area Weather Radar—Identifying significant factors affecting the calibration

    NASA Astrophysics Data System (ADS)

    Pedersen, Lisbeth; Jensen, Niels Einar; Madsen, Henrik

    2010-07-01

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

  6. Real-time areal precipitation determination from radar by means of statistical objective analysis

    NASA Astrophysics Data System (ADS)

    Gerstner, E.-M.; Heinemann, G.

    2008-05-01

    SummaryPrecipitation measurement by radar allows for areal rainfall determination with a high spatial and temporal resolution. However, hydrological applications require an accuracy of the precipitation quantification which cannot be obtained by today's weather radar devices. The quality of the radar-derived precipitation can be significantly improved with the aid of ground measurements. In this paper, a complete processing pipeline for real-time radar precipitation determination using a modified statistical objective analysis method is presented. Thereby, several additional algorithms, such as a dynamical use of Z-R relationships, a bias correction and an advection correction scheme are employed. The performance of the algorithms is tested for several case studies. For an error analysis, an eight months data set of X-band radar scans and rain gauge precipitation measurements is used. We show a reduction in the radar-rain gauge RMS difference of up to 59% for the optimal combination of the different algorithms.

  7. The Weather Radar Toolkit, National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center's support of interoperability and the Global Earth Observation System of Systems (GEOSS)

    NASA Astrophysics Data System (ADS)

    Ansari, S.; Del Greco, S.

    2006-12-01

    In February 2005, 61 countries around the World agreed on a 10 year plan to work towards building open systems for sharing geospatial data and services across different platforms worldwide. This system is known as the Global Earth Observation System of Systems (GEOSS). The objective of GEOSS focuses on easy access to environmental data and interoperability across different systems allowing participating countries to measure the "pulse" of the planet in an effort to advance society. In support of GEOSS goals, NOAA's National Climatic Data Center (NCDC) has developed radar visualization and data exporter tools in an open systems environment. The NCDC Weather Radar Toolkit (WRT) loads Weather Surveillance Radar 1988 Doppler (WSR-88D) volume scan (S-band) data, known as Level-II, and derived products, known as Level-III, into an Open Geospatial Consortium (OGC) compliant environment. The application is written entirely in Java and will run on any Java- supported platform including Windows, Macintosh and Linux/Unix. The application is launched via Java Web Start and runs on the client machine while accessing these data locally or remotely from the NCDC archive, NOAA FTP server or any URL or THREDDS Data Server. The WRT allows the data to be manipulated to create custom mosaics, composites and precipitation estimates. The WRT Viewer provides tools for custom data overlays, Web Map Service backgrounds, animations and basic filtering. The export of images and movies is provided in multiple formats. The WRT Data Exporter allows for data export in both vector polygon (Shapefile, Well-Known Text) and raster (GeoTIFF, ESRI Grid, VTK, NetCDF, GrADS) formats. By decoding the various Radar formats into the NetCDF Common Data Model, the exported NetCDF data becomes interoperable with existing software packages including THREDDS Data Server and the Integrated Data Viewer (IDV). The NCDC recently partnered with NOAA's National Severe Storms Lab (NSSL) to decode Sigmet C-band Doppler

  8. Remote sensing of rainfall for flash flood prediction in the United States

    NASA Astrophysics Data System (ADS)

    Gourley, J. J.; Flamig, Z.; Vergara, H. J.; Clark, R. A.; Kirstetter, P.; Terti, G.; Hong, Y.; Howard, K.

    2015-12-01

    This presentation will briefly describe the Multi-Radar Multi-Sensor (MRMS) system that ingests all NEXRAD and Canadian weather radar data and produces accurate rainfall estimates at 1-km resolution every 2 min. This real-time system, which was recently transitioned for operational use in the National Weather Service, provides forcing to a suite of flash flood prediction tools. The Flooded Locations and Simulated Hydrographs (FLASH) project provides 6-hr forecasts of impending flash flooding across the US at the same 1-km grid cell resolution as the MRMS rainfall forcing. This presentation will describe the ensemble hydrologic modeling framework, provide an evaluation at gauged basins over a 10-year period, and show the FLASH tools' performance during the record-setting floods in Oklahoma and Texas in May and June 2015.

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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

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

    USGS Publications Warehouse

    Mead, Reginald; Paxton, John; Sojda, Richard S.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.

    2010-01-01

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

  17. 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.

  18. Doppler radar results

    NASA Technical Reports Server (NTRS)

    Bracalente, Emedio M.

    1992-01-01

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

  19. Evaluating the potential of X-band polarimetric radar observations in mountainous hydrology

    NASA Astrophysics Data System (ADS)

    Anagnostou, Marios; Kalogiros, John; Nikolopoulos, Efthymios; Anagnostou, Emmanouil; Marra, Francesco; Mair, Elisabeth; Bertolidi, Giacomo; Tappeiner, Ulrike; Borga, Marco

    2013-04-01

    Alpine catchments hydrology is strongly determined by orographic effects on the space-time structure of precipitation. Mountain precipitation results from a multitude of processes such as mechanical lifting, enhancement, shadowing etc. Many of these processes are poorly understood, especially at small spatial and temporal scales. Consequently, this limits the predictive capability of hydrological models and our understanding of the majority of the precipitation-related natural hazards occurring in both high- and lowlands. This lack of knowledge is mainly due to the intrinsic limitations of our best measurement techniques: raingauges and weather radars. Raingauges provide relatively accurate but only point-like observations, while weather radars produce instantaneous spatially distributed rainfall maps but their operation over complex terrain creates a number of limitations, which make their estimates reliable in a limited space-time domain. A solution to this limitation might be the use of a number of cost-effective short-range X-band radars as complement to raingauges and conventional, large and expensive weather radars. The study focuses on a 64 km2 mountainous basin located in Northern Italy. Rainfall observations from a dense network of raingauges located at different elevation, a C-band and an X-band polarimetric mobile unit are used to force a semi-distributed hydrologic model. A number of storm events are simulated and compared to investigate the potential of using high-res rainfall input from X-band polarimetric radar for simulating the hydrologic response. Events have been discriminated on the basis of rainfall intensity, snowfall limit and hydrological response. Results reveal that in contrast with the other two rainfall sources, X-band observations offer an improved representation of orographic enhancement of precipitation, which turns to have a significant impact in simulating peak flows.

  20. The proposed flatland radar

    NASA Technical Reports Server (NTRS)

    Green, J. L.; Gage, K. S.; Vanzandt, T. E.; Nastrom, G. D.

    1986-01-01

    A flexible very high frequency (VHF) stratosphere-troposphere (ST) radar configured for meteorological research is to be constructed near Urbana, Illinois. Measurement of small vertical velocities associated with synoptic-scale meteorology can be performed. A large Doppler microwave radar (CHILL) is located a few km from the site of the proposed ST radar. Since the microwave radar can measure the location and velocity of hydrometeors and the VHF ST radar can measure clear (or cloudy) air velocities, simultaneous observations by these two radars of stratiform or convective weather systems would provide valuable meteorological information.

  1. Rainfall and temperature distinguish between Karnal bunt positive and negative years in wheat fields in Texas.

    PubMed

    Workneh, F; Allen, T W; Nash, G H; Narasimhan, B; Srinivasan, R; Rush, C M

    2008-01-01

    Karnal bunt of wheat, caused by the fungus Tilletia indica, is an internationally regulated disease. Since its first detection in central Texas in 1997, regions in which the disease was detected have been under strict federal quarantine regulations resulting in significant economic losses. A study was conducted to determine the effect of weather factors on incidence of the disease since its first detection in Texas. Weather variables (temperature and rainfall amount and frequency) were collected and used as predictors in discriminant analysis for classifying bunt-positive and -negative fields using incidence data for 1997 and 2000 to 2003 in San Saba County. Rainfall amount and frequency were obtained from radar (Doppler radar) measurements. The three weather variables correctly classified 100% of the cases into bunt-positive or -negative fields during the specific period overlapping the stage of wheat susceptibility (boot to soft dough) in the region. A linear discriminant-function model then was developed for use in classification of new weather variables into the bunt occurrence groups (+ or -). The model was evaluated using weather data for 2004 to 2006 for San Saba area (central Texas), and data for 2001 and 2002 for Olney area (north-central Texas). The model correctly predicted bunt occurrence in all cases except for the year 2004. The model was also evaluated for site-specific prediction of the disease using radar rainfall data and in most cases provided similar results as the regional level evaluation. The humid thermal index (HTI) model (widely used for assessing risk of Karnal bunt) agreed with our model in all cases in the regional level evaluation, including the year 2004 for the San Saba area, except for the Olney area where it incorrectly predicted weather conditions in 2001 as unfavorable. The current model has a potential to be used in a spray advisory program in regulated wheat fields. PMID:18943243

  2. Comparison of TOPMODEL streamflow simulations using NEXRAD-based and measured rainfall data, McTier Creek watershed, South Carolina

    USGS Publications Warehouse

    Feaster, Toby D.; Westcott, Nancy E.; Hudson, Robert J.M.; Conrads, Paul A.; Bradley, Paul M.

    2012-01-01

    Rainfall is an important forcing function in most watershed models. As part of a previous investigation to assess interactions among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations in the Edisto River Basin, the topography-based hydrological model (TOPMODEL) was applied in the McTier Creek watershed in Aiken County, South Carolina. Measured rainfall data from six National Weather Service (NWS) Cooperative (COOP) stations surrounding the McTier Creek watershed were used to calibrate the McTier Creek TOPMODEL. Since the 1990s, the next generation weather radar (NEXRAD) has provided rainfall estimates at a finer spatial and temporal resolution than the NWS COOP network. For this investigation, NEXRAD-based rainfall data were generated at the NWS COOP stations and compared with measured rainfall data for the period June 13, 2007, to September 30, 2009. Likewise, these NEXRAD-based rainfall data were used with TOPMODEL to simulate streamflow in the McTier Creek watershed and then compared with the simulations made using measured rainfall data. NEXRAD-based rainfall data for non-zero rainfall days were lower than measured rainfall data at all six NWS COOP locations. The total number of concurrent days for which both measured and NEXRAD-based data were available at the COOP stations ranged from 501 to 833, the number of non-zero days ranged from 139 to 209, and the total difference in rainfall ranged from -1.3 to -21.6 inches. With the calibrated TOPMODEL, simulations using NEXRAD-based rainfall data and those using measured rainfall data produce similar results with respect to matching the timing and shape of the hydrographs. Comparison of the bias, which is the mean of the residuals between observed and simulated streamflow, however, reveals that simulations using NEXRAD-based rainfall tended to underpredict streamflow overall. Given that the total NEXRAD-based rainfall data for the simulation period is lower than the

  3. Airborne rain mapping radar

    NASA Technical Reports Server (NTRS)

    Wilson, W. J.; Parks, G. S.; Li, F. K.; Im, K. E.; Howard, R. J.

    1988-01-01

    An airborne scanning radar system for remote rain mapping is described. The airborne rain mapping radar is composed of two radar frequency channels at 13.8 and 24.1 GHz. The radar is proposed to scan its antenna beam over + or - 20 deg from the antenna boresight; have a swath width of 7 km; a horizontal spatial resolution at nadir of about 500 m; and a range resolution of 120 m. The radar is designed to be applicable for retrieving rainfall rates from 0.1-60 mm/hr at the earth's surface, and for measuring linear polarization signatures and raindrop's fall velocity.

  4. 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.

  5. Minimizing uncertainty of daily rainfall interpolation over large catchments through realistic sampling of anisotropic correlogram parameters

    NASA Astrophysics Data System (ADS)

    Gyasi-Agyei, Yeboah

    2016-04-01

    It has been established that daily rainfall gauged network density is not adequate for the level of hydrological modelling required of large catchments involving pollutant and sediment transport, such as the catchments draining the coastal regions of Queensland, Australia, to the sensitive Great Barrier Reef. This paper seeks to establish a link between the spatial structure of radar and gauge rainfall for improved interpolation of the limited gauged data over a grid or functional units of catchments in regions with or without radar records. The study area is within Mt. Stapylton weather radar station range, a 128 km square region for calibration and validation, and the Brisbane river catchment for validation only. Two time periods (2000-01-01 to 2008-12-31 and 2009-01-01 to 2015-06-30) were considered, the later period for calibration when radar records were available and both time periods for validation without regard to radar information. Anisotropic correlograms of both the gauged and radar data were developed and used to establish the linkage required for areas without radar records. The maximum daily temperature significantly influenced the distributional parameters of the linkage. While the gauged, radar and sampled correlogram parameters reproduced the mean estimates similarly using leave-one-out cross-validation of Ordinary Kriging, the gauged parameters overestimated the standard deviation (SD) which reflects uncertainty by over 91% of cases compared with the radar or the sampled parameter sets. However, the distribution of the SD generated by the radar and the sampled correlogram parameters could not be distinguished, with a Kolmogorov-Smirnov test p-value of 0.52. For the validation case with the catchment, the percentage overestimation of SD by the gauged parameter sets decreased to 81.2% and 87.1% for the earlier and later time periods, respectively. It is observed that the extreme wet days' parameters and statistics were fairly widely distributed

  6. 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

  7. Calibration of the Z-R equation for a polarimetric radar located in Sabancuy, Mexico.

    NASA Astrophysics Data System (ADS)

    Noe Paredes-Victoria, Pedro; Rico-Ramirez, Miguel Angel; Pedrozo-Acuña, Adrian

    2016-04-01

    Rainfall estimation using weather radar has been the keystone in several hydrometeorological applications (Bringi & Chandrasekar, 2001) such as flood forecasting and water balance analysis. Additionally, in large spatiotemporal scales, an integrated network of weather radars provide an invaluable quantity of measured data to be applied to regional studies (Kitchen et al., 1994; Westrick et al., 1999). However, each radar must be individually analysed because the characteristics of calibration and local issues are unique and, therefore require further research (Krajewski and Smith, 1991). For instance, the rainfall rate R and the radar reflectivity Z are represented for the total number of a finite number of drops in a volume of scan and it has been demonstrated that these variables can be expressed into a nonlinear representation Z-R (Marshall & Palmer, 1948) and this relationship is unique and depends on the study region and the type of precipitation. In this study we used data from the Sabancuy-radar located in Campeche, Mexico (Latitude +18.9724, Longitude -91.1726) to estimate rainfall distributions into the convective contour in the Gulf of Mexico. This area counts with a long history of tropical storms and hurricanes which produce extreme rainfall causing flood events and important socioeconomic damages into this region. Therefore, the weather radar calibration and Z-R relationship was achieved applying current methodologies (e.g. Probability Matching Method, PMM) and using raingauges in two different temporal scales (daily and each 10 minutes). Thus, rainfall estimations using weather radar can be used to quantitative evaluate the accuracy of parametrizations of atmospheric models and also the results are particularly useful for error analysis in hydrometeorological modelling (Smith et al., 1975; Sun & Crook., 1997). Finally, a better estimation of rainfall in time and space (and forecasting: in short and long term) is a valuable source of information (Jones

  8. Urban Modification of Rainfall: St. Louis Revisited

    NASA Astrophysics Data System (ADS)

    Smith, J. A.; Baeck, M. L.; Yang, L.; Zhou, Z.; Signell, J.; Schleiss, M.

    2015-12-01

    In this study, the impacts of urbanization on rainfall are examined through analyses of high-resolution radar rainfall fields developed for the St. Louis metropolitan region. The objective of this study is to characterize the impacts of urbanization on the spatial and temporal distribution of rainfall from flood-producing storm systems. Analyses are based on rainfall fields for the period 2000 - 2015 with 1 km horizontal resolution and 15-minute time resolution. Rainfall fields are developed using the Hydro-NEXRAD algorithms. We will compare results based on analyses of "recent" St. Louis radar rainfall fields with results from the METROMEX experiment. We will also compare and contrast results for St. Louis with analyses based on radar rainfall fields from other urban regions.

  9. Landslide triggering rainfall thresholds estimation using hydrological modelling of catchments in the Ialomita Subcarpathians, Romania

    NASA Astrophysics Data System (ADS)

    Chitu, Zenaida; Busuioc, Aristita; Burcea, Sorin; Sandric, Ionut

    2016-04-01

    This work focuses on the hydro-meteorological analysis for landslide triggering rainfall thresholds estimation in the Ialomita Subcarpathians. This specific area is a complex geological and geomorphic unit in Romania, affected by landslides that produce numerous damages to the infrastructure every few years (1997, 1998, 2005, 2006, 2010, 2012 and 2014). Semi-distributed ModClark hydrological model implemented in HEC HMS software that integrates radar rainfall data, was used to investigate hydrological conditions within the catchment responsible for the occurrence of landslides during the main rainfall events. Statistical analysis of the main hydro-meteorological variables during the landslide events that occurred between 2005 and 2014 was carried out in order to identify preliminary rainfall thresholds for landslides in the Ialomita Subcarpathians. Moreover, according to the environmental catchment characteristics, different hydrological behaviors could be identified based on the spatially distributed rainfall estimates from weather radar data. Two hydrological regimes in the catchments were distinguished: one dominated by direct flow that explains the landslides that occurred due to slope undercutting and one characterized by high soil water storage during prolonged rainfall and therefore where subsurface runoff is significant. The hydrological precipitation-discharge modelling of the catchment in the Ialomita Subcarpathians, in which landslides occurred, helped understanding the landslide triggering and as such can be of added value for landslide research.

  10. Comparison of TRMM Precipitation Radar and Airborne Radar Data.

    NASA Astrophysics Data System (ADS)

    Durden, S. L.; Im, E.; Haddad, Z. S.; Li, L.

    2003-06-01

    The first spaceborne weather radar is the precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM), which was launched in 1997. As part of the TRMM calibration and validation effort, an airborne rain-mapping radar (ARMAR) was used to make underflights of TRMM during the B portion of the Texas and Florida Underflights (TEFLUN-B) and the third Convection and Moisture Experiment (CAMEX-3) in 1998 and the Kwajalein Experiment (KWAJEX) in 1999. The TRMM PR and ARMAR both operate at 14 GHz, and both instruments use a downward-looking, cross-track scanning geometry, which allows direct comparison of data. Nearly simultaneous PR and ARMAR data were acquired in seven separate cases. These data are compared to examine the effects of larger resolution volume and lower sensitivity in the PR data relative to ARMAR. The PR and ARMAR data show similar structures, although the PR data tend to have lower maximum reflectivities and path attenuations because of nonuniform beam-filling effects. Nonuniform beam filling can also cause a bias in the observed path attenuation relative to that corresponding to the beam-averaged rain rate. The PR rain-type classification is usually consistent with the ARMAR data.

  11. Application of merged satellite and radar data for flood risk reduction in urban area

    NASA Astrophysics Data System (ADS)

    Park, K.; Yoon, S.; Jang, S.; Lee, S.

    2015-12-01

    The natural disaster from heavy rainfall and Typhoon are increased damage of property and human life in urban area with the impact of climate change. Therefore the accurate observation and short-term forecast of heavy rainfall by multi-sensor is very important for reduce damage from severe storms and Typhoon. This study develops flash warning systems based on Communication, Ocean and Meteorological Satellite(COMS) geostationary satellite data and ground radar. The proposed system has been developed blending rainfall forecasting highly time and space resolution successive the brightness temperatures(TBs) from IR image of COMS with rain/no-rain classification of ground s-band radar. This system was evaluated to case study of the sudden rainstorms by the Automated Weather System(AWS) around Korea peninsular on summer season.

  12. Ground validation of satellite measurements of precipitation using upgraded dual polarization WSR-88D radar network

    NASA Astrophysics Data System (ADS)

    Chen, H.; Chandrasekar, C. V.

    2013-12-01

    The Global Precipitation Measurement (GPM) core satellite is scheduled for launch in February 2014, just a couple of months after the AGU's 2013 annual fall meeting. The GPM mission is expected to provide accurate and frequent observations of global precipitation which will play an important role in improving weather, climate, and hydrological prediction capabilities. As an indispensable part of GPM mission, ground validation will focus on the demonstration and evaluation of space based precipitation classification and retrieval algorithms. Among various validation tools, dual-polarization radar is a powerful equipment that can be used for accurate surface rainfall measurement. Recently, the Next-Generation Radar (NEXRAD) network has been upgraded with dual-polarization capabilities. The polarization diversity radars have great potential for understanding the precipitation microphysics and cross validation of space based observations. For direct comparison between space- and ground-based radar systems, Bolen and Chandrasekar (2003) proposed a methodology to align the measurement from these two systems. This alignment method has shown a great superiority by comparing the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) reflectivity measurements and ground radar observations. This paper will first present the rationale and opportunities of the usage of dual-polarization radar in validation of GPM precipitation retrieval algorithms. The main focus will be on the dual-polarization based rainfall microphysics retrievals, including the rain drop size distribution (DSD), quantitative precipitation estimation, and hydrometeor classifications. Dual-polarization radar observations from the WSR-88D network will be used extensively, especially when there are satellite overpasses during the post launch ear of GPM, for cross-validating the DSD retrieval algorithms and rainfall relations in different climatological regions. The dual-polarization algorithm for

  13. 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

  14. Probabilistic rainfall warning system with an interactive user interface

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    A real time 24/7 automatic alert system is in operational use at the Finnish Meteorological Institute (FMI). It consists of gridded forecasts of the exceedance probabilities of rainfall class thresholds in the continuous lead time range of 1 hour to 5 days. Nowcasting up to six hours applies ensemble member extrapolations of weather radar measurements. With 2.8 GHz processors using 8 threads it takes about 20 seconds to generate 51 radar based ensemble members in a grid of 760 x 1226 points. Nowcasting exploits also lightning density and satellite based pseudo rainfall estimates. The latter ones utilize convective rain rate (CRR) estimate from Meteosat Second Generation. The extrapolation technique applies atmospheric motion vectors (AMV) originally developed for upper wind estimation with satellite images. Exceedance probabilities of four rainfall accumulation categories are computed for the future 1 h and 6 h periods and they are updated every 15 minutes. For longer forecasts exceedance probabilities are calculated for future 6 and 24 h periods during the next 4 days. From approximately 1 hour to 2 days Poor man's Ensemble Prediction System (PEPS) is used applying e.g. the high resolution short range Numerical Weather Prediction models HIRLAM and AROME. The longest forecasts apply EPS data from the European Centre for Medium Range Weather Forecasts (ECMWF). The blending of the ensemble sets from the various forecast sources is performed applying mixing of accumulations with equal exceedance probabilities. The blending system contains a real time adaptive estimator of the predictability of radar based extrapolations. The uncompressed output data are written to file for each member, having total size of 10 GB. Ensemble data from other sources (satellite, lightning, NWP) are converted to the same geometry as the radar data and blended as was explained above. A verification system utilizing telemetering rain gauges has been established. Alert dissemination e.g. for

  15. 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

  16. 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.

  17. Validation of Simulated Hurricane Drop Size Distributions using Polarimetric Radar

    NASA Astrophysics Data System (ADS)

    Bell, M. M.; Brown, B. R.; Frambach, A. J.

    2015-12-01

    Recent upgrades to the U.S. radar network now allow for polarimetric measurements of landfalling hurricanes, providing a new dataset to validate cloud microphysical parameterizations used in tropical cyclone simulations. Polarimetric radar variables 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, asymmetric distributions of precipitation, and the approximate intensity of the storms. However, most of the schemes produced a higher frequency of larger raindrops than observed. The Thompson aerosol-aware bulk and a spectral bin microphysical (SBM) scheme showed the best fidelity to the observed joint probability distribution of horizontal and differential reflectivity. The SBM also produced the most accurate intensity and lowest rainfall accumulation, but required much higher computational resources than the bulk schemes.

  18. Development of the Application techniques for KMA dual-pol. radar network in Korea

    NASA Astrophysics Data System (ADS)

    Suk, Mi-Kyung; Nam, Kyung-Yeub; Jung, Sung-A.; Ko, Jeong-Seok

    2016-04-01

    Korea is located between the Eurasian continent and Northwestern pacific. So East Asian Monsoon affects the country every season and every year with the rainy season (Chang-ma front), convective stroms, snow storms, and sometimes typhoons. Korea Meteorological Administration (KMA) has been operating many kinds of meteorological observation networks, including 10 operational radars and 1 testbed radar. Weather Radar Center (WRC) of Korea Meteorological Administration (KMA) performs a task of development and application of cross governmental dual-pol. radar harmonization for the effective use of the national resources from 2013 since the tri-agencies (KMA, Ministry of Land, Infrastructure and Transport, Ministry of National Defense) singed the MOU for the co-utilization of cross governmental dual-pol. radar. This task develops the techniques of the high-quality data processing, the support of the forecasting, etc. The techniques of the high-quality data processing are the quality control for the removal of non-meteorological echoes, the classification of the hydrometeors. The techniques for support of the forecasting are the computation and verification of the rainfall estimation of dual-pol. and single-pol. radars, etc. And it is developed the application techniques by using Yong-In Testbed dual-pol. radar, the merged rainfall field of the radars and the satellites, etc. Further works are the computation of the high-resolution 3-dimensional wind field, the quantitative precipitation forecasting, the development of the application and the information service techniques for the hydrology, climate, industry, aviation for the prevention techniques against the severe weather by using multi-wavelengths ( X, C, S-band radars) of the cross governments, etc.

  19. Comparison of atmospheric instability indices derived from radiosonde observations and precipitation values measured with a weather radar and a rain gauge network in Sao Paulo, Brazil.

    NASA Astrophysics Data System (ADS)

    Alves, Mauro; Martin, Inacio; Shkevov, Rumen; Gusev, Anatoly; De Abreu, Alessandro

    2016-07-01

    Radio soundings are carried out daily in more than 800 stations throughout the world. The data collected in the soundings are used in many meteorological applications such as numerical weather prediction and climate models. Despite the relatively large number of sounding stations, they are unevenly distributed over the globe. It is generally assumed that the desired distance between stations is 300 km. In this study, we performed a comparison of 20 soundings of two stations located 85 km apart (State of São Paulo, Brazil; 23.511811° S, 46.637528° W, and 23.212578° S, 45.866581° W) to determine whether there is a concordance between atmospheric instability indices derived from the data collected by soundings at the these different locations. Additionally, precipitation data obtained by a meteorological radar and a rain gauge network during the same period as the soundings are compared to the stability indices to establish a correlation between precipitation values and these indices.

  20. 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.

  1. 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

  2. Values of Deploying a Compact Polarimetric Radar to Monitor Extreme Precipitation in a Mountainous Area: Mineral County, Colorado

    NASA Astrophysics Data System (ADS)

    Cheong, B. L.; Kirstetter, P. E.; Yu, T. Y.; Busto, J.; Speeze, T.; Dennis, J.

    2015-12-01

    Precipitation in mountainous regions can trigger flash floods and landslides especially in areas affected by wildfire. Because of the small space-time scales required for observation, they remain poorly observed. A light-weighted X-band polarimetric radar can rapidly respond to the situation and provide continuous rainfall information with high resolution for flood forecast and emergency management. A preliminary assessment of added values to the operational practice in Mineral county, Colorado was performed in Fall 2014 and Summer 2015 with a transportable polarimetric radar deployed at the Lobo Overlook. This region is one of the numerous areas in the Rocky Mountains where the WSR-88D network does not provide sufficient weather coverage due to blockages, and the limitations have impeded forecasters and local emergency managers from making accurate predictions and issuing weather warnings. High resolution observations were collected to document the precipitation characteristics and demonstrate the added values of deploying a small weather radar in such context. The analysis of the detailed vertical structure of precipitation explain the decreased signal sampled by the operational radars. The specific microphysics analyzed though polarimetry suggest that the operational Z-R relationships may not be appropriate to monitor severe weather over this wildfire affected region. Collaboration with the local emergency managers and the National Weather Service shows the critical value of deploying mobile, polarimetric and unmanned radars in complex terrain. Several selected cases are provided in this paper for illustration.

  3. 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.

  4. 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.

  5. 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

  6. Weather Information System

    NASA Technical Reports Server (NTRS)

    1995-01-01

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

  7. 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

  8. Forecast of muddy floods using high-resolution radar precipitation forcasting data and erosion modelling

    NASA Astrophysics Data System (ADS)

    Hänsel, Phoebe; Schindewolf, Marcus; Schmidt, Jürgen

    2016-04-01

    In the federal province of Saxony, Eastern Germany, almost 60 % of the agricultural land is endangered by erosion processes, mainly caused by heavy rainfall events. Beside the primary impact of soil loss and decreasing soil fertility, erosion can cause significant effects if transported sediments are entering downslope settlements, infrastructure or traffic routes. Available radar precipitation data are closing the gap between the conventional rainfall point measurements and enable the nationwide rainfall distribution with high spatial and temporal resolution. By means of the radar precipitation data of the German Weather Service (DWD), high-resolution radar-based rainfall data totals up to 5 minute time steps are possible. The radar data are visualised in a grid-based hourly precipitation map. In particular, the daily and hourly precipitation maps help to identify regions with heavy rainfall and possible erosion events. In case of an erosion event on agricultural land, these areas are mapped with an unmanned airborne vehicle (UAV). The camera-equipped UAV delivers high-resolution images of the erosion event, that allow the generation of high-resolution orthophotos. By the application of the high-resolution radar precipitation data as an input for the process-based soil loss and deposition model EROSION 3D, these images are for validation purposes. Future research is focused on large scale soil erosion modelling with the help of the radar forecasting product and an automatic identification of sediment pass over points. The study will end up with an user friendly muddy flood warning tool, which allows the local authorities to initiate immediate measures in order to prevent severe damages in settlements, infrastructure or traffic routes.

  9. Rainfall simulation in education

    NASA Astrophysics Data System (ADS)

    Peters, Piet; Baartman, Jantiene; Gooren, Harm; Keesstra, Saskia

    2016-04-01

    Rainfall simulation has become an important method for the assessment of soil erosion and soil hydrological processes. For students, rainfall simulation offers an year-round, attractive and active way of experiencing water erosion, while not being dependent on (outdoors) weather conditions. Moreover, using rainfall simulation devices, they can play around with different conditions, including rainfall duration, intensity, soil type, soil cover, soil and water conservation measures, etc. and evaluate their effect on erosion and sediment transport. Rainfall simulators differ in design and scale. At Wageningen University, both BSc and MSc student of the curriculum 'International Land and Water Management' work with different types of rainfall simulation devices in three courses: - A mini rainfall simulator (0.0625m2) is used in the BSc level course 'Introduction to Land Degradation and Remediation'. Groups of students take the mini rainfall simulator with them to a nearby field location and test it for different soil types, varying from clay to more sandy, slope angles and vegetation or litter cover. The groups decide among themselves which factors they want to test and they compare their results and discuss advantage and disadvantage of the mini-rainfall simulator. - A medium sized rainfall simulator (0.238 m2) is used in the MSc level course 'Sustainable Land and Water Management', which is a field practical in Eastern Spain. In this course, a group of students has to develop their own research project and design their field measurement campaign using the transportable rainfall simulator. - Wageningen University has its own large rainfall simulation laboratory, in which a 15 m2 rainfall simulation facility is available for research. In the BSc level course 'Land and Water Engineering' Student groups will build slopes in the rainfall simulator in specially prepared containers. Aim is to experience the behaviour of different soil types or slope angles when (heavy) rain

  10. 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

  11. 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.

  12. TRMM radar

    NASA Technical Reports Server (NTRS)

    Okamoto, Kenichi

    1993-01-01

    The results of a conceptual design study and the performance of key components of the Bread Board Model (BBM) of the Tropical Rainfall Measuring Mission (TRMM) radar are presented. The radar, which operates at 13.8 GHz and is designed to meet TRMM mission objectives, has a minimum measurable rain rate of 0.5 mm/h with a range resolution of 250 m, a horizontal resolution of about 4 km, and a swath width of 220 km. A 128-element active phased array system is adopted to achieve contiguous scanning within the swath. The basic characteristics of BBM were confirmed by experiments. The development of EM started with the cooperation of NASDA and CRL.

  13. 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 classify cloud types, which revealed that low clouds occurred most frequently.

  14. A semi-urban case study of small scale variability of rainfall and run-off, with C- and X-band radars and the fully distributed hydrological model Multi-Hydro

    NASA Astrophysics Data System (ADS)

    Alves de Souza, Bianca; da Silva Rocha Paz, Igor; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel

    2016-04-01

    The complexity of urban hydrology results both from that of urban systems and the extreme rainfall variability. The latter can display strongly localised rain cells that can be extremely damaging when hitting vulnerable parts of urban systems. This paper investigates this complexity on a semi-urban sub-catchment - located in Massy (South of Paris, France) - of the Bievre river, which is known for its frequent flashfloods. Advanced geo-processing techniques were used to find the ideal pixel size for this 6.326km2 basin. C-band and X-band radar data are multifractally downscaled at various resolutions and input to the fully distributed hydrological model Multi-Hydro. The latter has been developed at Ecole des Ponts ParisTech. It integrates validated modules dealing with surface flow, saturated and unsaturated surface flow, and sewer flow. The C-band radar is located in Trappes, approx. 21km East of the catchment, is operated by Méteo-France and has a resolution of 1km x 1km x 5min. The X-band radar operated by Ecole des Ponts Paris Tech on its campus has a resolution of 125m x 125m x 3.4min. The performed multifractal downscaling enables both the generation of large ensemble realizations and easy change of resolution (e.g. down to 10 m in the present study). This in turn allows a detailed analysis of the impacts of small scale variability and the required resolution to obtain accurate simulations, therefore predictions. This will be shown on two rainy episodes over the chosen sub-catchment of the Bievre river.

  15. Understanding and optimizing microstrip patch antenna cross polarization radiation on element level for demanding phased array antennas in weather radar applications

    NASA Astrophysics Data System (ADS)

    Vollbracht, D.

    2015-11-01

    The antenna cross polarization suppression (CPS) is of significant importance for the accurate calculation of polarimetric weather radar moments. State-of-the-art reflector antennas fulfill these requirements, but phased array antennas are changing their CPS during the main beam shift, off-broadside direction. Since the cross polarization (x-pol) of the array pattern is affected by the x-pol element factor, the single antenna element should be designed for maximum CPS, not only at broadside, but also for the complete angular electronic scan (e-scan) range of the phased array antenna main beam positions. Different methods for reducing the x-pol radiation from microstrip patch antenna elements, available from literature sources, are discussed and summarized. The potential x-pol sources from probe fed microstrip patch antennas are investigated. Due to the lack of literature references, circular and square shaped X-Band radiators are compared in their x-pol performance and the microstrip patch antenna size variation was analyzed for improved x-pol pattern. Furthermore, the most promising technique for the reduction of x-pol radiation, namely "differential feeding with two RF signals 180° out of phase", is compared to single fed patch antennas and thoroughly investigated for phased array applications with simulation results from CST MICROWAVE STUDIO (CST MWS). A new explanation for the excellent port isolation of dual linear polarized and differential fed patch antennas is given graphically. The antenna radiation pattern from single fed and differential fed microstrip patch antennas are analyzed and the shapes of the x-pol patterns are discussed with the well-known cavity model. Moreover, two new visual based electromagnetic approaches for the explanation of the x-pol generation will be given: the field line approach and the surface current distribution approach provide new insight in understanding the generation of x-pol component in microstrip patch antenna radiation

  16. GPM Movie of Souledor's Rainfall Structure

    NASA Video Gallery

    On Aug. 5, the GPM satellite data was used to make a 3-D vertical structure of rainfall within Soudelor. Some storms examined with GPM's radar reached heights of over 12.9 km (about 8 miles) and we...

  17. Urban High-Resolution Precipitation Product: Combining C-Band and Local X-Band Radar Data

    NASA Astrophysics Data System (ADS)

    Lengfeld, Katharina; Clemens, Marco; Münster, Hans; Ament, Felix

    2014-05-01

    Modelling precipitation induced floods and their impact on flood-prone regions is one of the biggest challenges for hydrometeorological forecasters. The largest source of error in flood forecasting systems is uncertainty in precipitation estimation. In state of the art rainfall-runoff models, precipitation fields from C-band radars are used as input with temporal resolution in the order of 5 minutes and spatial resolution in the order of kilometres. These radars cannot observe the small scale structure of rain events that influences runoff especially in impermeable urban areas. Therefore, precipitation fields with higher spatial and temporal resolution would improve flood forecasting. In recent years radar systems operating in the X-band frequency range have been developed to provide precipitation fields for areas of special interest in higher temporal (1 min or below) and higher spatial resolution (250 m or below) in complementation to nationwide radar networks. However single X-band radars are highly influenced by attenuation. Within the project Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) the University of Hamburg and the Max-Planck-Institute for Meteorology operate a single X-band radar covering the city of Hamburg, Germany. The radar provides precipitation fields with temporal resolution of 30 s and range resolution of 60 m. The area is also covered by the C-band radar Fuhlsbüttel operated by the German Weather Service (DWD) that gives precipitation estimates with a temporal resolution of 5 min and a range resolution of 1 km. We will introduce a method to merge the precipitation fields derived from the X-band radar into the precipitation field provided by the C-band radar Fuhlsbüttel. The observations of radar Fuhlsbüttel will also be integrated in the correction of the attenuated measurements of the X-band radar. The merged precipitation field of both radars will be a valid product to improve rainfall

  18. TRMM Data from the Goddard Earth Sciences (GES) DISC DAAC: Tropical Rainfall Measuring Mission (TRMM)

    NASA Technical Reports Server (NTRS)

    2003-01-01

    Tropical rainfall affects the lives and economies 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. 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. It is currently in its fifth year of operation. Data generated from TRMM and archived at the GES DAAC 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.

  19. Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project

    NASA Astrophysics Data System (ADS)

    Picciotti, E.; Marzano, F. S.; Anagnostou, E. N.; Kalogiros, J.; Fessas, Y.; Volpi, A.; Cazac, V.; Pace, R.; Cinque, G.; Bernardini, L.; De Sanctis, K.; Di Fabio, S.; Montopoli, M.; Anagnostou, M. N.; Telleschi, A.; Dimitriou, E.; Stella, J.

    2013-05-01

    Hydro-meteorological hazards like convective outbreaks leading to torrential rain and floods are among the most critical environmental issues world-wide. In that context weather radar observations have proven to be very useful in providing information on the spatial distribution of rainfall that can support early warning of floods. However, quantitative precipitation estimation by radar is subjected to many limitations and uncertainties. The use of dual-polarization at high frequency (i.e. X-band) has proven particularly useful for mitigating some of the limitation of operational systems, by exploiting the benefit of easiness to transport and deploy and the high spatial and temporal resolution achievable at small antenna sizes. New developments on X-band dual-polarization technology in recent years have received the interest of scientific and operational communities in these systems. New enterprises are focusing on the advancement of cost-efficient mini-radar network technology, based on high-frequency (mainly X-band) and low-power weather radar systems for weather monitoring and hydro-meteorological forecasting. Within the above context, the main objective of the HYDRORAD project was the development of an innovative integrated decision support tool for weather monitoring and hydro-meteorological applications. The integrated system tool is based on a polarimetric X-band mini-radar network which is the core of the decision support tool, a novel radar products generator and a hydro-meteorological forecast modelling system that ingests mini-radar rainfall products to forecast precipitation and floods. The radar products generator includes algorithms for attenuation correction, hydrometeor classification, a vertical profile reflectivity correction, a new polarimetric rainfall estimators developed for mini-radar observations, and short-term nowcasting of convective cells. The hydro-meteorological modelling system includes the Mesoscale Model 5 (MM5) and the Army Corps

  20. Changes in the TRMM Version-5 and Version-6 Precipitation Radar Products Due to Orbit Boost

    NASA Technical Reports Server (NTRS)

    Liao, Liang; Meneghini, Robert

    2010-01-01

    The performance of the version-5 and version-6 Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) products before and after the satellite orbit boost is assessed through a series of comparisons with Weather Surveillance Radar (WSR)-88D ground-based radar in Melbourne, Florida. Analysis of the comparisons of radar reflectivity near the storm top from the ground radar and both versions of the PR indicates that the PR bias relative to the WSR radar at Melbourne is on the order of 1dB for both pre- and post-boost periods, indicating that the PR products maintain accurate calibration after the orbit boost. Comparisons with the WSR-88D near-surface reflectivity factors indicate that both versions of the PR products accurately correct for attenuation in stratiform rain. However, in convective rain, both versions exhibit negative biases in the near-surface radar reflectivity with version-6 products having larger negative biases than version-5. Rain rate comparisons between the ground and space radars show similar characteristics

  1. Cross-validation of spaceborne radar and ground polarimetric radar observations

    NASA Astrophysics Data System (ADS)

    Bolen, Steven Matthew

    There is great potential for spaceborne weather radar to make significant observations of the precipitating medium on global scales. The Tropical Rainfall Mapping Mission (TRMM) is the first mission dedicated to measuring rainfall in the tropics 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 at 350 km altitude and 35 degree inclination. 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, which can be as high as 10--15 dB. This can seriously impair the accuracy of rain rate retrieval algorithms derived from PR returns. Direct inter-comparison of meteorological measurements between space and ground radar observations can be used to evaluate spaceborne processing algorithms. Though conceptually straightforward, this can be a challenging task. Differences in viewing aspects between space and earth point observations, propagation frequencies, resolution volume size and time synchronization mismatch between measurements can contribute to direct point-by-point inter-comparison errors. The problem is further complicated by spatial geometric distortions induced into the space-based observations caused by the movements and attitude perturbations of the spacecraft itself. A method is developed to align space and ground radar observations so that a point-by-point inter-comparison of measurements can be made. Ground-based polarimetric observations are used to estimate the attenuation of PR signal returns along individual PR beams, and a technique is formulated to determine the true PR return from GR measurements via theoretical modeling of specific attenuation (k) at PR wavelength with ground-based S-band radar observations. The statistical behavior of the parameters

  2. Non-stationarity in intermittent rainfall: the 'dry drift'

    NASA Astrophysics Data System (ADS)

    Schleiss, M.; Berne, A.

    2013-12-01

    The non-stationary nature of intermittent rainfall is investigated. It manifests itself in the fact that the average rain rate changes with the distance to the closest dry area. This fundamental link between the average rainfall intensity and the rainfall occurrence process is called the 'dry drift'. The present contribution aims to analyze and model this dry drift using observations from disdrometers and weather radar. The results show that dry drifts are very general features of precipitation that extend between 5-10 kilometers in space and 15-30 minutes in time. More importantly, dry drifts also affect the drop size distribution (DSD). Indeed, both the average drop concentration Nt [m-3] and the average drop size Dm [mm] significantly decrease when approaching a dry region/period. Most of the time, however, the dry drift in Nt is much stronger than the dry drift in Dm. This has some important consequences in remote sensing and means, in particular, that the prefactor and the exponent of the Z-R relationship can change when approaching the border of a rain cell. Because dry drifts are an important source of non-stationarity, it is also important to take them into account when disaggregating large scale rainfall fields for hydrological applications. The authors provide some examples of this problem and discuss possible ways of addressing it.

  3. Using Satellite Rainfall for Simulation of Flash Floods in Mountainous Basins

    NASA Astrophysics Data System (ADS)

    Anagnostou, Emmanouil; Nikolopoulos, Efthymios; Bartsotas, Nikolaos; Solomos, Stavros; Kallos, George

    2013-04-01

    Effective flash flood warning procedures are usually hampered by observational limitations of precipitation over mountainous basins where flash floods occur. Satellite rainfall estimates are available over complex terrain regions offering a potentially viable solution to the observational coverage problem. However, satellite estimates of heavy rainfall rates are associated with significant biases and random errors that non-linearly propagate in hydrologic modeling imposing severe limitations on the use of these products in flood forecasting. 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 flash floods over complex terrain basins. The study uses major flash flood events on medium size mountainous basins (600-1500 km2) in Northern Italian Alps. Comparison of satellite-rainfall with rainfall derived from gauge-calibrated weather radar estimates showed that although satellite products suffer from large biases they could represent the temporal variability of basin-averaged precipitation. Propagation of satellite-rainfall through a hydrologic model revealed that systematic error in 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. Overall, this study highlights the use of high-resolution NWP analysis for improving satellite-rainfall retrieval to allow a more appropriate use of satellite-rainfall products in flash-flood applications of complex terrain basins.

  4. Effects of Tunable Data Compression on Geophysical Products Retrieved from Surface Radar Observations with Applications to Spaceborne Meteorological Radars

    NASA Technical Reports Server (NTRS)

    Gabriel, Philip M.; Yeh, Penshu; Tsay, Si-Chee

    2013-01-01

    This paper presents results and analyses of applying an international space data compression standard to weather radar measurements that can easily span 8 orders of magnitude and typically require a large storage capacity as well as significant bandwidth for transmission. By varying the degree of the data compression, we analyzed the non-linear response of models that relate measured radar reflectivity and/or Doppler spectra to the moments and properties of the particle size distribution characterizing clouds and precipitation. Preliminary results for the meteorologically important phenomena of clouds and light rain indicate that for a 0.5 dB calibration uncertainty, typical for the ground-based pulsed-Doppler 94 GHz (or 3.2 mm, W-band) weather radar used as a proxy for spaceborne radar in this study, a lossless compression ratio of only 1.2 is achievable. However, further analyses of the non-linear response of various models of rainfall rate, liquid water content and median volume diameter show that a lossy data compression ratio exceeding 15 is realizable. The exploratory analyses presented are relevant to future satellite missions, where the transmission bandwidth is premium and storage requirements of vast volumes of data, potentially problematic.

  5. Weather Specialist/Aerographer's Mate.

    ERIC Educational Resources Information Center

    Chanute AFB Technical Training Center, IL.

    This course trains Air Force personnel to perform duties prescribed for weather specialists and aerographer's mates. Training includes meteorology, surface and ship observation, weather radar, operation of standard weather instruments and communications equipment, and decoding and plotting of surface and upper air codes upon standard maps and…

  6. Wageningen Urban Rainfall Experiment 2014 (WURex14): Experimental setup and preliminary results

    NASA Astrophysics Data System (ADS)

    van Leth, Thomas C.; Uijlenhoet, Remko; Overeem, Aart; Leijnse, Hidde; Hazenberg, Pieter; Berne, Alexis

    2016-04-01

    Microwave links from cellular communication networks have been shown to be able to provide valuable information concerning the space-time variability of rainfall. In particular over urban areas, where network densities are generally high, they have the potential to complement existing dedicated infrastructure to measure rainfall (gauges, radars). In addition, microwave links provide a great opportunity for ground-based rainfall measurement for those land surface areas of the world where gauges and radars are generally lacking. Such information is not only crucial for water management and agriculture, but also for instance for ground validation of space-borne rainfall estimates such as those provided by the GPM (Global Precipitation Measurement) mission. WURex14 is dedicated to address several errors and uncertainties associated with such quantitative precipitation estimates in detail. The core of the experiment is provided by three co-located microwave links installed between two major buildings on the Wageningen University campus, approximately 2 km apart: a 38 GHz commercial microwave link, provided by T-Mobile NL, and 26 GHz and 38 GHz (dual-polarization) research microwave links from RAL. Transmitting and receiving antennas have been attached to masts installed on the roofs of the two buildings, about 30 m above the ground. This setup has been complemented with a Scintec infrared Large-Aperture Scintillometer, installed over the same path, as well as 5 Parsivel optical disdrometers and an automated rain gauge positioned at several locations along the path. Temporal sampling of the received signals was performed at a rate of 20 Hz. The setup is being monitored by time-lapse cameras to assess the state of the antennas as well as the atmosphere. Finally, data is available from the KNMI weather radars and an automated weather station situated just outside Wageningen. The experiment has been active between August 2014 and December 2015. We give a global overview of

  7. LDAR observations of a developing thunderstorm correlated with field mill, ground strike location, and weather radar data including the first report of the design and capabilities of a new, time-of-arrival Ground-strike Location System (GSLS)

    NASA Technical Reports Server (NTRS)

    Poehler, H. A.

    1978-01-01

    An experiment designed to observe and measure a thunderstorm prior to, during, and after its development over the Kennedy Space Center was successful. Correlated measurements of airborne field strength, ground-based field strength, LDAR lightning discharge location in the clouds, weather radar percipitation echoes, plus ground strike location with the new KSC Ground Strike Location System (GSLS) were gathered, and reported. This test marks the first operational use of the GSLS System, and this report contains the first report of its design and capabilities.

  8. Radar-driven high-resolution hydro-meteorological forecasts of the 26 September 2007 Venice flash flood

    NASA Astrophysics Data System (ADS)

    Rossa, Andrea M.; Laudanna Del Guerra, Franco; Borga, Marco; Zanon, Francesco; Settin, Tommaso; Leuenberger, Daniel

    2010-11-01

    SummaryThis study aims to assess the feasibility of assimilating carefully checked radar rainfall estimates into a numerical weather prediction (NWP) to extend the forecasting lead time for an extreme flash flood. The hydro-meteorological modeling chain includes the convection-permitting NWP model COSMO-2 and a coupled hydrological-hydraulic model. Radar rainfall estimates are assimilated into the NWP model via the latent heat nudging method. The study is focused on 26 September 2007 extreme flash flood which impacted the coastal area of North-eastern Italy around Venice. The hydro-meteorological modeling system is implemented over the 90 km2 Dese river basin draining to the Venice Lagoon. The radar rainfall observations are carefully checked for artifacts, including rain-induced signal attenuation, by means of physics-based correction procedures and comparison with a dense network of raingauges. The impact of the radar rainfall estimates in the assimilation cycle of the NWP model is very significant. The main individual organized convective systems are successfully introduced into the model state, both in terms of timing and localization. Also, high-intensity incorrectly localized precipitation is correctly reduced to about the observed levels. On the other hand, the highest rainfall intensities computed after assimilation underestimate the observed values by 20% and 50% at a scale of 20 km and 5 km, respectively. The positive impact of assimilating radar rainfall estimates is carried over into the free forecast for about 2-5 h, depending on when the forecast was started. The positive impact is larger when the main mesoscale convective system is present in the initial conditions. The improvements in the precipitation forecasts are propagated to the river flow simulations, with an extension of the forecasting lead time up to 3 h.

  9. An Experimental Study of the Rainfall Variability Within TRMM/GPM Precipitation Radar and Microwave Sensor Instantaneous Field of View During MC3E

    NASA Technical Reports Server (NTRS)

    Tokay, Ali; Petersen, Walter Arthur; Gatlin, Patrick N.; Wingo, Matt; Wolff, David B.; Carey, Lawrence D.

    2011-01-01

    Dual tipping bucket gauges were operated at 16 sites in support of ground based precipitation measurements during Mid-latitude Continental Convective Clouds Experiment (MC3E). The experiment is conducted in North Central Oklahoma from April 22 through June 6, 2011. The gauge sites were distributed around Atmospheric Radiation Measurement (ARM) Climate Research facility where the minimum and maximum separation distances ranged from 1 to 12 km. This study investigates the rainfall variability by employing the stretched exponential function. It will focus on the quantitative assessment of the partial beam of the experiment area in both convective and stratiform rain. The parameters of the exponential function will also be determined for various events. This study is unique for two reasons. First is the existing gauge setup and the second is the highly convective nature of the events with rain rates well above 100 mm/h for 20 minutes. We will compare the findings with previous studies.

  10. An Experimental Study of the Rainfall Variability Within TRMM/GPM Precipitation Radar and Microwave Sensor Instantaneous Field of View During MC3E

    NASA Technical Reports Server (NTRS)

    Tokay, Ali; Petersen, Arthur; Gatlin, Patrick N.; Wingo, Matt; Wolff, David B.; Carey, Lawrence D.

    2011-01-01

    Dual tipping bucket gauges were operated at 16 sites in support of ground based precipitation measurements during Mid-latitude Continental Convective Clouds Experiment (MC3E). The experiment is conducted in North Central Oklahoma from April 22 through June 6, 2011. The gauge sites were distributed around Atmospheric Radiation Measurement (ARM) Climate Research facility where the minimum and maximum separation distances ranged from 1 to 12 km. This study investigates the rainfall variability by employing the stretched exponential function. It will focus on the quantitative assessment of the partial beam of the experiment area in both convective and stratiform rain. The parameters of the exponential function will also be determined for various events. This study is unique for two reasons. First is the existing gauge setup and the second is the highly convective nature of the events with rain rates well above 100 mm h-1 for 20 minutes. We will compare the findings with previous studies.

  11. GMS-based"Future Time" Rainfall Data Assimilation for Mesoscale Weather Prediction over Korean Peninsula and Future Prospects with GPM Satellite Measurements

    NASA Technical Reports Server (NTRS)

    Smith, Eric A.; Ou, Mi-Lim

    2004-01-01

    This study examines the use of satellite-derived nowcasted (short-term forecasted) rainfall over 3-hour time periods to gain an equivalent time increment in initializing a nonhydrostatic mesoscale model used for predicting convective rainfall events over the Korean peninsula. Infrared (IR) window measurements from the Japanese Geostationary Meteorological Satellite (GMS) are used to specify latent heating for a spinup period of the model - but in future time -- thus initializing in advance of actual time in the framework of a prediction scenario. The main scientific objective of the study is to investigate the strengths and weaknesses of this approach insofar as data assimilation, in which the nowcasted assimilation data are derived independently of the prognostic model itself. Although there have been various recent improvements in formulating the dynamics, thermodynamics, and microphysics of mesoscale models, as well as computer advances which allow the use of high resolution cloud-resolving grids and explicit latent heating over regional domains, spinup remains at the forefront of unresolved mesoscale modeling problems. In general, non-realistic spinup limits the skill in predicting the spatial-temporal distribution of convection and precipitation, primarily in the early hours of a. forecast, stemming from standard prognostic variables not representing the initial diabatic heating field produced by the ambient convection and cloud fields. The long-term goal of this research is to improve short-range (12-hour) quantitative precipitation forecasting (QPF) over the Korean peninsula through the use of innovative data assimilation methods based on geosynchronous satellite measurements. As a step in ths direction, a non-standard data assimilation experiment in conjunction with GMS-retrieved nowcasted rainfall information introduced to the mesoscale model is conducted. The 3-hourly precipitation forecast information is assimilated through nudging the associated

  12. Quality control of rainfall measurements in Cyprus

    NASA Astrophysics Data System (ADS)

    Golz, Claudia; Einfalt, Thomas; Michaelides, Silas Chr.

    The basic condition for using precipitation data from raingauges and radars is data quality control. This aspect is important for comparing and using rainfall data, for example in models. In the scope of the EU-project VOLTAIRE (Validation of multisensors precipitation fields and numerical modelling in Mediterranean test sites) rain data from Cyprus have been analysed. Different quality control methods have been applied to the rainfall data of 158 raingauges and the data of 11 events (in 2002 and 2003) of the C-Band radar in Kykkos. The first results of the use of ground clutter algorithms for radar data in Cyprus are presented in the paper.

  13. Rainy Day: A Remote Sensing-Driven Extreme Rainfall Simulation Approach for Hazard Assessment

    NASA Astrophysics Data System (ADS)

    Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold

    2015-04-01

    Progress on the assessment of rainfall-driven hazards such as floods and landslides has been hampered by the challenge of characterizing the frequency, intensity, and structure of extreme rainfall at the watershed or hillslope scale. Conventional approaches rely on simplifying assumptions and are strongly dependent on the location, the availability of long-term rain gage measurements, and the subjectivity of the analyst. Regional and global-scale rainfall remote sensing products provide an alternative, but are limited by relatively short (~15-year) observational records. To overcome this, we have coupled these remote sensing products with a space-time resampling framework known as stochastic storm transposition (SST). SST "lengthens" the rainfall record by resampling from a catalog of observed storms from a user-defined region, effectively recreating the regional extreme rainfall hydroclimate. This coupling has been codified in Rainy Day, a Python-based platform for quickly generating large numbers of probabilistic extreme rainfall "scenarios" at any point on the globe. Rainy Day is readily compatible with any gridded rainfall dataset. The user can optionally incorporate regional rain gage or weather radar measurements for bias correction using the Precipitation Uncertainties for Satellite Hydrology (PUSH) framework. Results from Rainy Day using the CMORPH satellite precipitation product are compared with local observations in two examples. The first example is peak discharge estimation in a medium-sized (~4000 square km) watershed in the central United States performed using CUENCAS, a parsimonious physically-based distributed hydrologic model. The second example is rainfall frequency analysis for Saint Lucia, a small volcanic island in the eastern Caribbean that is prone to landslides and flash floods. The distinct rainfall hydroclimates of the two example sites illustrate the flexibility of the approach and its usefulness for hazard analysis in data-poor regions.

  14. Dynamical linkage of tropical and subtropical weather systems to the intraseasonal oscillations of the Indian summer monsoon rainfall. Part II: Simulations in the ENSEMBLES project

    NASA Astrophysics Data System (ADS)

    Ma, Shujie; Rodó, Xavier; Song, Yongjia; Cash, Benjamin A.

    2012-09-01

    We assess the ability of individual models (single-model ensembles) and the multi-model ensemble (MME) in the European Union-funded ENSEMBLES project to simulate the intraseasonal oscillations (ISOs; specifically in 10-20-day and 30-50-day frequency bands) of the Indian summer monsoon rainfall (ISMR) over the Western Ghats (WG) and the Bay of Bengal (BoB), respectively. This assessment is made on the basis of the dynamical linkages identified from the analysis of observations in a companion study to this work. In general, all models show reasonable skill in simulating the active and break cycles of the 30-50-day ISOs over the Indian summer monsoon region. This skill is closely associated with the proper reproduction of both the northward propagation of the intertropical convergence zone (ITCZ) and the variations of monsoon circulation in this band. However, the models do not manage to correctly simulate the eastward propagation of the 30-50-day ISOs in the western/central tropical Pacific and the eastward extension of the ITCZ in a northwest to southeast tilt. This limitation is closely associated with a limited capacity of models to accurately reproduce the magnitudes of intraseasonal anomalies of both the ITCZ in the Asian tropical summer monsoon regions and trade winds in the tropical Pacific. Poor reproduction of the activity of the western Pacific subtropical high on intraseasonal time scales also amplify this limitation. Conversely, the models make good reproduction of the WG 10-20-day ISOs. This success is closely related to good performance of the models in the representation of the northward propagation of the ITCZ, which is partially promoted by local air-sea interactions in the Indian Ocean in this higher-frequency band. Although the feature of westward propagation is generally represented in the simulated BoB 10-20-day ISOs, the air-sea interactions in the Indian Ocean are spuriously active in the models. This leads to active WG rainfall, which is not

  15. Machine learning methods for the classification of extreme rainfall and hail events

    NASA Astrophysics Data System (ADS)

    Teschl, Reinhard; Süsser-Rechberger, Barbara; Paulitsch, Helmut

    2015-04-01

    In this study, an analysis of a meteorological data set with machine learning tools is presented. The aim was to identify characteristic patterns in different sources of remote sensing data that are associated with hazards like extreme rainfall and hail. The data set originates from a project that was started in 2007 with the goal to document and mitigate hail events in the province of Styria, Austria. It consists of three dimensional weather radar data from a C-band Doppler radar, cloud top temperature information from infrared channels of a weather satellite, as well as the height of the 0° C isotherm from the forecast of the national weather service. The 3D radar dataset has a spatial resolution of 1 km x 1 km x 1 km, up to a height of 16 km above mean sea level, and a temporal resolution of 5 minutes. The infrared satellite image resolution is about 3 km x 3 km, the images are updated every 30 minutes. The study area has approx. 16,000 square kilometers. So far, different criteria for the occurrence of hail (and its discrimination from heavy rain) have been found and are documented in the literature. When applying these criteria to our data and contrasting them with damage reports from an insurance company, a need for adaption was identified. Here we are using supervised learning paradigms to find tailored relationships for the study area, validated by a sub-dataset that was not involved in the training process.

  16. Climatology of Vertical Air Motion During Rainfall in Niamey, Niger and Black Forest, Germany using an Innovative Cloud Radar Retrieval Technique

    NASA Astrophysics Data System (ADS)

    Luke, E. P.; Giangrande, S. E.; Kollias, P.

    2008-12-01

    In recent years, the DOE Atmospheric Radiation Measurement (ARM) program has deployed its ARM Mobile Facility (AMF) to collect continuous measurements in several climatologically distinct locations, including a year-long stay in Niamey, Niger and eight months in Germany's Black Forest. The AMF includes a vertically pointing 95 GHz cloud radar, a tool of choice for profiling non-precipitating clouds at high spatial and temporal resolutions, but commonly considered poorly suited to the quantitative study of precipitation, due in large part to attenuation. However, an innovative technique first explored by Lhermitte in the late 1980s, and subsequently by others, sidesteps much of the quantitative uncertainty imposed by attenuation by exploiting non-Rayleigh resonance effects of scattering from raindrops at 95 GHz. Given a modest range of suitable drop sizes, non-Rayleigh resonances appear as distinct peaks and valleys in Doppler spectra, which once identified, can be directly mapped to known drop sizes by Mie theory. Although attenuation in rain at 95 GHz is substantial, key to the technique is that all non-Rayleigh peaks and valleys in a given Doppler spectrum are affected equally, preserving their relative positions and magnitudes (barring feature extinction). Vertical air motion is retrieved very accurately by taking the difference between the measured Doppler velocity of a resonance feature (usually the first valley) and the known terminal velocity of its associated drop size. We have achieved promising retrieval accuracies at spatial and temporal resolutions of 30 meters and 2 seconds. Here we present lessons learned when the retrieval technique is automated and applied to measurements taken in rain over the full durations of the Niamey and Black Forest AMF deployments, comparing vertical air velocity patterns of monsoonal precipitation over the African desert with those of the orographically influenced precipitation in Germany's mountains.

  17. Model analysis of radar echo split observed in an artificial cloud seeding experiment

    NASA Astrophysics Data System (ADS)

    Masaki, Shimada; Kikuro, Tomine; Koji, Nishiyama

    2016-06-01

    An artificial cloud seeding experiment was performed over the Japan Sea in winter to show how massive seeding could be effective to mitigate heavy snowfall damage. The results showed that 20 min after cloud seeding, a portion of the radar echo beneath the seeding track was weakened to divide the radar echo into two parts. In order to analyze the results, a numerical simulation was conducted by using the Weather Research and Forecasting model verion 3.5.1. In this simulation, the seeding effects were represented as phenomena capable of changing rain particles by accreting cloud ice and snow to form graupel particles and by changing cloud liquid water to snow particles. The graupel particles fell rapidly, thus temporarily intensifying the rainfall, which subsequently decreased. Therefore, the weakened radar echo in the field experiment is deemed to have been caused by the increase in rapidly falling graupel particles.

  18. Classification and correction of the radar bright band with polarimetric radar

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

    The annular region of enhanced radar reflectivity, known as the Bright Band (BB), occurs when the radar beam intersects a layer of melting hydrometeors. Radar reflectivity is related to rainfall through a power law equation and so this enhanced region can lead to overestimations of rainfall by a factor of up to 5, so it is important to correct for this. The BB region can be identified by using several techniques including hydrometeor classification and freezing level forecasts from mesoscale meteorological models. Advances in dual-polarisation radar measurements and continued research in the field has led to increased accuracy in the ability to identify the melting snow region. A method proposed by Kitchen et al (1994), a form of which is currently used operationally in the UK, utilises idealised Vertical Profiles of Reflectivity (VPR) to correct for the BB enhancement. A simpler and more computationally efficient method involves the formation of an average VPR from multiple elevations for correction that can still cause a significant decrease in error (Vignal 2000). The purpose of this research is to evaluate a method that relies only on analysis of measurements from an operational C-band polarimetric radar without the need for computationally expensive models. Initial results show that LDR is a strong classifier of melting snow with a high Critical Success Index of 97% when compared to the other variables. An algorithm based on idealised VPRs resulted in the largest decrease in error when BB corrected scans are compared to rain gauges and to lower level scans with a reduction in RMSE of 61% for rain-rate measurements. References Kitchen, M., R. Brown, and A. G. Davies, 1994: Real-time correction of weather radar data for the effects of bright band, range and orographic growth in widespread precipitation. Q.J.R. Meteorol. Soc., 120, 1231-1254. Vignal, B. et al, 2000: Three methods to determine profiles of reflectivity from volumetric radar data to correct

  19. 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, Ismail; Onen, Alper; Yilmaz, Koray; Gochis, David

    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. The study then undertook a comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow. Several flood events that occurred in the Black Sea region were used for testing and evaluation. 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, 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

  20. Location-Based Rainfall Nowcasting Service for Public

    NASA Astrophysics Data System (ADS)

    Woo, Wang-chun

    2013-04-01

    The Hong Kong Observatory has developed the "Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS)", a radar-based rainfall nowcasting system originally to support forecasters in rainstorm warning and severe weather forecasting such as hail, lightning and strong wind gusts in Hong Kong. The system has since been extended to provide rainfall nowcast service direct for the public in recent years. Following the launch of "Rainfall Nowcast for the Pearl River Delta Region" service provided via a Geographical Information System (GIS) platform in 2008, a location-based rainfall nowcast service served through "MyObservatory", a smartphone app for iOS and Android developed by the Observatory, debuted in September 2012. The new service takes advantage of the capability of smartphones to detect own locations and utilizes the quantitative precipitation forecast (QPF) from SWIRLS to provide location-based rainfall nowcast to the public. The conversion of radar reflectivity data (at 2 or 3 km above ground) to rainfall in SWIRLS is based on the Z-R relationship (Z=aRb) with dynamical calibration of the coefficients a and b determined using real-time rain gauge data. Adopting the "Multi-scale Optical-flow by Variational Analysis (MOVA)" scheme to track the movement of radar echoes and Semi-Lagrangian Advection (SLA) scheme to extrapolate their movement, the system is capable of producing QPF for the next six hours in a grid of 480 x 480 that covers a domain of 256 km x 256 km once every 6 minutes. Referencing the closest point in a resampled 2-km grid over the territory of Hong Kong, a prediction as to whether there will be rainfall exceeding 0.5 mm in every 30 minute intervals for the next two hours at users' own or designated locations are made available to the users in both textual and graphical format. For those users who have opted to receive notifications, a message would pop up on the user's phone whenever rain is predicted in the next two hours in a user