Liu, J.; Bray, M.; Han, D.
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 curves and the rainfall totals which have direct impact on rainfall-runoff transformation in hydrological applications. It is found that by solely assimilating radar data, the improvement of rainfall forecasts are not as obvious as assimilating meteorological data; whereas the positive effect of radar data can be seen when combined with the traditional meteorological data, which leads to the best rainfall forecasts among the five modes. To further improve the effect of radar data assimilation, limitations of the radar correction ratio developed in this study is discussed and suggestions are made on more efficient utilisation of radar data in NWP assimilation.
Hamidi, A.; Devineni, N.; Zahraei, A.; Khanbilvardi, R.
Information on the probability of extreme rainfall events of various durations is required for hydraulic design in order to control storm runoff. Such information is usually expressed as a relationship between Intensity-Duration-Frequency (IDF) of extreme rainfall. The general IDF curve approach assumes a stationary climate and typically is regionalized based on small number of gauges. However, with the ongoing accumulation of weather radar records, radar-rainfall data represent an alternative to gauging data providing much needed spatial resolution. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. The Next Generation Weather Radar system (NEXRAD) comprises of 160 Weather Surveillance Radar-1988 Doppler (WSR-88D) sites throughout the United States and at selected overseas locations. Stage IV is a national multi-sensor radar product from NCEP, mosaicked from the regional multi-sensor analyses with 4km×4km and 1h resolution of space and time respectively. In the current study, 11 years of HRAP (Hydrologic Rainfall Analysis Project) gridded Stage IV radar data is employed to generate a relationship between intensity, duration, frequency and the storm exposed area of New York Metropolitan area covering almost 30,000 km2 of the most populous cities at the east part of United States. We investigate the statistical properties of the spatial manifestation of the rainfall exceedances and present the scaling phenomena of contiguous flooded areas as a result of large scale organization of storms. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional analysis can be developed. In this project, we explore a non-parametric multivariate approach and a parametric Bayesian approach to develop stochastic scenarios of spatial extreme rainfall fields for regional risk assessment.
Dai, Qiang; Zhuo, Lu; Han, Dawei
With the rapidly growth of urbanization and population, the decision making for managing urban flood risk has been a significant issue for most large cities in China. A high-quality measurement of rainfall at small temporal but large spatial scales is of great importance to urban flood risk management. Weather radar rainfall, with its advantage of short-term predictability and high spatial and temporal resolutions, has been widely applied in the urban drainage system modeling. It is recognized that weather radar is subjected to many uncertainties and many studies have been carried out to quantify these uncertainties in order to improve the quality of the rainfall and the corresponding outlet flow. However, considering the final action in urban flood risk management is the decision making such as flood warning and whether to build or how to operate a hydraulics structure, some uncertainties of weather radar may have little or significant influence to the final results. For this reason, in this study, we aim to investigate which characteristics of the radar rainfall are the significant ones for decision making in urban flood risk management. A radar probabilistic quantitative rainfall estimated scheme is integrated with an urban flood model (Storm Water Management Model, SWMM) to make a decision on whether to warn or not according to the decision criterions. A number of scenarios with different storm types, synoptic regime and spatial and temporal correlation are designed to analyze the relationship between these affected factors and the final decision. Based on this, parameterized radar probabilistic rainfall estimation model is established which reflects the most important elements in the decision making for urban flood risk management.
Bruni, G.; ten Veldhuis, J. A. E.; Otto, T.; Leijnse, H.
Urban hydrological modelling requires high resolution rainfall data to be able to simulate fast runoff processes and related short response times. Over the last three decades, rainfall input into urban hydrological and hydrodynamic models has often been restricted to a single rain gauge in or near the catchment, rendering rainfall input one of the main sources of uncertainty in model calculations. In recent years, rainfall data from weather radars that provide space-time estimates of rainfall are becoming increasingly available. C-band and S-band radars have been used for operational precipitation measurements and offer spatial resolutions of 1km2 to several km2. This resolution is still insufficient to meet the relevant scales of urban hydrology (e.g. Berne et al. 2004; Emmanuel et al., 2011, Schellart et al., in press). Higher spatial resolution rainfall measurements can be provided by X-band radars, especially at short range where attenuation is not yet a major factor. At the Cabauw Experimental Site for Atmospheric Research (CESAR), an X-band Doppler polarimetric radar has been installed as well as a dense network of rain gauges (Leijnse et al., 2010). Data from the C-band Doppler radar at 25 km distance are also available for this site. A network of 11 rain gauges is to be installed in the city area as well as a network of water level sensors in the stormwater sewers. A selection of rain events is analysed based on the available rainfall measurement instruments for this site. The events are used as input into a hydrodynamic model of the sewer system of the city of Utrecht, located between CESAR and the C-band radar site. The effect of different spatial rainfall data resolutions and of rainfall data uncertainty on hydrological response will be analysed for various sizes of catchments within the Utrecht sewer system.
Mazza, Alessandro; Antonini, Andrea; Melani, Samantha; Ortolani, Alberto
In this work we propose a technique for 15-minutes cumulative rainfall mapping, applied over Tuscany, using Italian weather radar networks together with the regional rain gauge network. In order to assess the accuracy of the radar-based rainfall estimates, we have compared them with spatial coincident rain gauge measurements. Precipitation at ground is our target observable: rain gauge measurements of such parameter have a so small error that we consider it negligible (especially if compared from what retrievable from radars). In order to make comparable the observations given from these two types of sensors, we have collected cumulative rainfall over areas a few tens of kilometres wide. The method used to spatialise rain gauges data has been the Ordinary Block Kriging. In this case the comparison results have shown a good correlation between the cumulative rainfall obtained from the rain gauges and those obtained by the radar measurements. Such results are encouraging in the perspective of using the radar observations for near real time cumulative rainfall nowcasting purposes. In addition the joint use of satellite instruments as SEVIRI sensors on board of MSG-3 satellite can add relevant information on the nature, spatial distribution and temporal evolution of cloudiness over the area under study. For this issue we will analyse several MSG-3 channel images, which are related to cloud physical characteristics or ground features in case of clear sky.
Bassan, José Marcio; Martins, João Eduardo Machado Perea; Sugahara, Shigetoshi; da Silveira, Reinaldo Bomfim
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.
Meteorological radar is a remote sensing system that provides rainfall estimations at high spatial and temporal resolution. The radar-based rainfall intensities (R) are calculated from the observed radar reflectivities (Z). In this paper we explore scale-dependency of the power-law Z-R parameters w...
W. F. Krajewski; J. A. Smith
Radar observations of rainfall and their use in hydrologic research provide the focus for the paper. Radar-rainfall products are crucial for input to runoff and flood prediction models, validation of satellite remote sensing algorithms, and for statistical characterization of extreme rainfall frequency. In this context we discuss the issues of radar-rainfall product development, and the theoretical and practical requirements of
Hou, Tuanjie; Kong, Fanyou; Chen, Xunlai; Lei, Hengchi; Hu, Zhaoxia
To improve the accuracy of short-term (0-12 h) forecasts of severe weather in southern China, a real-time storm-scale forecasting system, the Hourly Assimilation and Prediction System (HAPS), has been implemented in Shenzhen, China. The forecasting system is characterized by combining the Advanced Research Weather Research and Forecasting (WRF-ARW) model and the Advanced Regional Prediction System (ARPS) three-dimensional variational data assimilation (3DVAR) package. It is capable of assimilating radar reflectivity and radial velocity data from multiple Doppler radars as well as surface automatic weather station (AWS) data. Experiments are designed to evaluate the impacts of data assimilation on quantitative precipitation forecasting (QPF) by studying a heavy rainfall event in southern China. The forecasts from these experiments are verified against radar, surface, and precipitation observations. Comparison of echo structure and accumulated precipitation suggests that radar data assimilation is useful in improving the short-term forecast by capturing the location and orientation of the band of accumulated rainfall. The assimilation of radar data improves the short-term precipitation forecast skill by up to 9 hours by producing more convection. The slight but generally positive impact that surface AWS data has on the forecast of near-surface variables can last up to 6-9 hours. The assimilation of AWS observations alone has some benefit for improving the Fractions Skill Score (FSS) and bias scores; when radar data are assimilated, the additional AWS data may increase the degree of rainfall overprediction.
Hazenberg, Pieter; Leijnse, Hidde; Uijlenhoet, Remko
Between 25 and 27 August 2010 a long-duration mesoscale convective system was observed above the Netherlands, locally giving rise to rainfall accumulations exceeding 150 mm. Correctly measuring the amount of precipitation during such an extreme event is important, both from a hydrological and meteorological perspective. Unfortunately, the operational weather radar measurements were affected by multiple sources of error and only 30% of the precipitation observed by rain gauges was estimated. Such an underestimation of heavy rainfall, albeit generally less strong than in this extreme case, is typical for operational weather radar in The Netherlands. In general weather radar measurement errors can be subdivided into two groups: (1) errors affecting the volumetric reflectivity measurements (e.g. ground clutter, radar calibration, vertical profile of reflectivity) and (2) errors resulting from variations in the raindrop size distribution that in turn result in incorrect rainfall intensity and attenuation estimates from observed reflectivity measurements. A stepwise procedure to correct for the first group of errors leads to large improvements in the quality of the estimated precipitation, increasing the radar rainfall accumulations to about 65% of those observed by gauges. To correct for the second group of errors, a coherent method is presented linking the parameters of the radar reflectivity-rain rate (Z-R) and radar reflectivity-specific attenuation (Z-k) relationships to the normalized drop size distribution (DSD). Two different procedures were applied. First, normalized DSD parameters for the whole event and for each precipitation type separately (convective, stratiform and undefined) were obtained using local disdrometer observations. Second, 10,000 randomly generated plausible normalized drop size distributions were used for rainfall estimation, to evaluate whether this Monte Carlo method would improve the quality of weather radar rainfall products. Using the disdrometer information, the best results were obtained in case no differentiation between precipitation type (convective, stratiform and undefined) was made, increasing the event accumulations to more than 80% of those observed by gauges. For the randomly optimized procedure, radar precipitation estimates further improve and closely resemble observations in case one differentiates between precipitation type. However, the optimal parameter sets are very different from those derived from disdrometer observations. It is therefore questionable if single disdrometer observations are suitable for large-scale quantitative precipitation estimation, especially if the disdrometer is located relatively far away from the main rain event, which was the case in this study. In conclusion, this study shows the benefit of applying detailed error correction methods to improve the quality of the weather radar product, but also confirms the need to be cautious using locally obtained disdrometer measurements.
This 2-hour module presents the fundamental principles of Doppler weather radar operation and how to interpret common weather phenomena using radar imagery. This is accomplished via conceptual animations and many interactive radar examples in which the user can practice interpreting both radar reflectivity and radar velocity imagery. Although intended as an accelerated introduction to understanding and using basic Doppler weather radar products, the module can also serve as an excellent refresher for more experienced users.
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.
Abancó, C.; Hürlimann, M.; Sempere, D.; Berenguer, M.
Torrential processes such as debris flows or hyperconcentrated flows are fast movements formed by a mix of water and different amounts of unsorted solid material. They occur in steep torrents and suppose a high risk for the human settlements. Rainfall is the most common triggering factor for debris flows. The rainfall threshold defines the rainfall conditions that, when reached or exceeded, are likely to provoke one or more events. Many different types of empirical rainfall thresholds for landslide triggering have been defined. Direct measurements of rainfall data are normally not available from a point next to or in the surroundings of the initiation area of the landslide. For this reason, most of the thresholds published for debris flows have been established by data measured at the nearest rain gauges (often located several km far from the landslide). Only in very few cases, the rainfall data to analyse the triggering conditions of the debris flows have been obtained by weather (Doppler) radar. Radar devices present certain limitations in mountainous regions due to undesired reboots, but their main advantage is that radar data can be obtained for any point of the territory. The objective of this work was to test the use of the weather radar data for the definition of rainfall thresholds for debris-flow triggering. Thus, rainfall data obtained from 3 to 5 rain gauges and from radar were compared for a dataset of events occurred in Catalonia (Spain). The goal was to determine in which cases the description of the rainfall episode (in particular the maximum intensity) had been more accurate. The analysed dataset consists of: 1) three events occurred in the Rebaixader debris-flow monitoring station (Axial Pyrenees) including two hyperconcentrated flows and one debris flow; 2) one debris-flow event occurred in the Port Ainé ski resort (Axial Pyrenees); 3) one debris-flow event in Montserrat (Mediterranean Coastal range). The comparison of the hyetographs from the different devices showed that the reliability of the radar is higher for short, high intensity storms more than for long lasting, medium intensity ones. Additionally, the best fit corresponds to the situations where the storm nucleus is located near the source area of the debris flow. The results of the comparison between different rain gauges show similar trends. The ones located in the same valley as the debris flow usually show good results, but if there are orographic elements in-between the debris-flow torrent and the rain gauge or the distance is large, the results can imply a great error in the definition of rainfall intensity. Therefore, we can state that the reliability of the use of the weather radar to define rainfall thresholds is strongly depending on the type of the storm and the distance between the source area and the nucleus of the storm.
Anggraheni, Evi; Payrastre, Olivier; Emmanuel, Isabelle; Andrieu, Herve
The consideration of spatial rainfall variability in hydrological modeling is not only an important scientific issue but also, with the current development of high resolution rainfall data from weather radars, an increasing request from managers of sewerage networks and from flood forecasting services. Although the literature on this topic is already significant, at this time the conclusions remain contrasted. The impact of spatial rainfall variability on the hydrological responses appears to highly depend both on the organization of rainfall fields and on the watershed characteristics. The objective of the study presented here is to confirm and analyze the high impact of spatial rainfall variability in the specific context of flash floods. The case study presented is located in the Gard region in south east of France and focuses on four events which occurred on 13 different watersheds in 2008. The hydrological behaviors of these watersheds have been represented by the distributed rainfall - runoff model CINECAR, which already proved to well represent the hydrological responses in this region (Naulin et al., 2013). The influence of spatial rainfall variability has been studied here by considering two different rainfall inputs: radar data with a resolution of 1 km x 1 km and the spatial average rainfall over the catchment. First, the comparison between simulated and measured hydrographs confirms the good performances of the model for intense rainfall events, independently of the level of spatial rainfall variability of these events. Secondly, the simulated hydrographs obtained from radar data are taken as reference and compared to those obtained from the average rainfall inputs by computing two values: the time difference and the difference of magnitude between the simulated peaks discharge. The results highly depend on the rainfall event considered, and on the level of organization of the spatial rainfall variability. According to the model, the behavior of the studied watersheds may sometimes remain very similar with a homogeneous rainfall input, whereas for some cases the differences in the peak discharges can reach up to 80%. A detailed analysis illustrates the possible role of the watershed in enhancing the effect of rainfall spatial variability. In a further step, the objective is to test the ability of four rainfall variability indicators to identify the situations for which spatial rainfall variability has the greatest influence on the watershed response. The selected indicators include those of Zoccatelli et al. (2010), and all rely on a detailed analysis of spatial rainfall organization in function of hydrological distances (i.e. the distances measured along the stream network from one point of the watershed to the outlet). The analysis of the links between these indicators and the hydrological behaviors identified is currently in progress. Reference: Naulin, J.P., Payrastre, O., Gaume, E., 2013. Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France. Journal of Hydrology, 486, 88-99, doi:10.1016/j.jhydrol.2013.01.044 Zoccatelli, D., Borga, M., Zanon, F., Antonescu, B., Stancalie, G., 2010. Which rainfall spatial information for flash flood response modelling? A numerical investigation based on data from the Carpathian range, Romania. Journal of Hydrology, 394, 148-161
Llasat, Maria-Carmen; Ceperuelo, Manuel; Rigo, Tomeu
The main objective of the present paper is to show a methodology for undertaking rainfall regionalization of a region taking into account the convective features of the precipitation, and useful for establishing homogeneous zones for improving the alert system. This methodology has been applied to a hydrographic region located in northeast Spain, with an area of 16000 km 2 and characterized by a highly contrasted topography. Information provided by meteorological radar and 5-min precipitation data for 126 automatic raingauges has been used for the period 1996-2002. The previous analysis done on the basis of the 1927-1981 rainfall rate series for the Jardí raingauge, located in Barcelona, has also been considered. To that end, the first step was to draw up a proposal for classification of the pluviometric episodes. Recourse was had for this purpose to definition of the ? parameter, related with the greater or lesser convective character of the event and calculated on the basis of the rainfall intensity at the surface ( Llasat, 2001) and, when data are available, on the basis of radar reflectivity. Results show that the threshold of 35 mm/h to characterize convective episodes from raingauge data can be corroborated from the radar point of view when convective precipitation is identified using 2-D algorithms with a reflectivity threshold of 43 dBZ. Once the soundness of the ? parameter had been corroborated, it was applied to more than 2900 precipitation episodes recorded in the region, in order to discriminate the features of the different subregions and their time and space distribution throughout the entire series of the samples. Using this definition, 92% of the precipitation events recorded in this region, with accumulated rainfall above 35 mm, are classified as convective ones, representing 95% of the precipitation amount. Application of the ? parameter combined with monthly rainfall data allows differentiation of 8 regions with different convective precipitation features.
Meneghini, Robert; Kozu, Toshiaki
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.
Liguori, S.; Rico-Ramirez, M. A.
The potential advantages resulting from integrating weather radar rainfall estimates in hydro-meteorological forecasting systems is limited by the inherent uncertainty affecting radar rainfall measurements, which is due to various sources of error [1-3]. The improvement of quality control and correction techniques is recognized to play a role for the future improvement of radar-based flow predictions. However, the knowledge of the uncertainty affecting radar rainfall data can also be effectively used to build a hydro-meteorological forecasting system in a probabilistic framework. This work discusses the results of the implementation of a novel probabilistic forecasting system developed to improve ensemble predictions over a small urban area located in the North of England. An ensemble of radar rainfall fields can be determined as the sum of a deterministic component and a perturbation field, the latter being informed by the knowledge of the spatial-temporal characteristics of the radar error assessed with reference to rain-gauges measurements. This approach is similar to the REAL system  developed for use in the Southern-Alps. The radar uncertainty estimate can then be propagated with a nowcasting model, used to extrapolate an ensemble of radar rainfall forecasts, which can ultimately drive hydrological ensemble predictions. A radar ensemble generator has been calibrated using radar rainfall data made available from the UK Met Office after applying post-processing and corrections algorithms [5-6]. One hour rainfall accumulations from 235 rain gauges recorded for the year 2007 have provided the reference to determine the radar error. Statistics describing the spatial characteristics of the error (i.e. mean and covariance) have been computed off-line at gauges location, along with the parameters describing the error temporal correlation. A system has then been set up to impose the space-time error properties to stochastic perturbations, generated in real-time at gauges location, and then interpolated back onto the radar domain, in order to obtain probabilistic radar rainfall fields in real time. The deterministic nowcasting model integrated in the STEPS system [7-8] has been used for the purpose of propagating the uncertainty and assessing the benefit of implementing the radar ensemble generator for probabilistic rainfall forecasts and ultimately sewer flow predictions. For this purpose, events representative of different types of precipitation (i.e. stratiform/convective) and significant at the urban catchment scale (i.e. in terms of sewer overflow within the urban drainage system) have been selected. As high spatial/temporal resolution is required to the forecasts for their use in urban areas [9-11], the probabilistic nowcasts have been set up to be produced at 1 km resolution and 5 min intervals. The forecasting chain is completed by a hydrodynamic model of the urban drainage network. The aim of this work is to discuss the implementation of this probabilistic system, which takes into account the radar error to characterize the forecast uncertainty, with consequent potential benefits in the management of urban systems. It will also allow a comparison with previous findings related to the analysis of different approaches to uncertainty estimation and quantification in terms of rainfall  and flows at the urban scale . Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and Dr. Alan Seed from the Australian Bureau of Meteorology for providing the radar data and the nowcasting model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1.
Integrated operation was simulated of ten dynamic combined sewer regulators on a Montreal interceptor. Detailed review of digital recording weather radar capabilities indicated that it is potentially the best rainfall estimation means for accomplishing the runoff prediction that ...
Noh, Hui-seong; Shin, Hyun-seok; Kang, Na-rae; Lee, Choong-Ke; Kim, Hung-soo
Recently, the necessity for rainfall estimation and forecasting using the radar is being highlighted, due to the frequent occurrence of torrential rainfall resulting from abnormal changes of weather. Radar rainfall data represents temporal and spatial distributions properly and replace the existing rain gauge networks. It is also frequently applied in many hydrologic field researches. However, the radar rainfall data has an accuracy limitation since it estimates rainfall, by monitoring clouds and precipitation particles formed around the surface of the earth(1.5-3km above the surface) or the atmosphere. In a condition like Korea where nearly 70% of the land is covered by mountainous areas, there are lots of restrictions to use rainfall radar, because of the occurrence of beam blocking areas by topography. This study is aiming at analyzing runoff and examining the applicability of (R(Z), R(ZDR) and R(KDP)) provided by the Han River Flood Control Office(HRFCO) based on the basin elevation of Nakdong river watershed. For this purpose, the amount of radar rainfall of each rainfall event was estimated according to three sub-basins of Nakdong river watershed with the average basin elevation above 400m which are Namgang dam, Andong dam and Hapcheon dam and also another three sub-basins with the average basin elevation below 150m which are Waegwan, Changryeong and Goryeong. After runoff analysis using a distribution model, Vflo model, the results were reviewed and compared with the observed runoff. This study estimated the rainfall by using the radar-rainfall transform formulas, (R(Z), R(Z,ZDR) and R(Z,ZDR,KDP) for four stormwater events and compared the results with the point rainfall of the rain gauge. As the result, it was overestimated or underestimated, depending on rainfall events. Also, calculation indicates that the values from R(Z,ZDR) and R(Z,ZDR,KDP) relatively showed the most similar results. Moreover the runoff analysis using the estimated radar rainfall is performed. Then hydrologic component of the runoff hydrographs, peak flows and total runoffs from the estimated rainfall and the observed rainfall are compared. The results show that hydrologic components have high fluctuations depending on storm rainfall event. Thus, it is necessary to choose appropriate radar rainfall data derived from the above radar rainfall transform formulas to analyze the runoff of radar rainfall. The simulated hydrograph by radar in the three basins of agricultural areas is more similar to the observed hydrograph than the other three basins of mountainous areas. Especially the peak flow and shape of hydrograph of the agricultural areas is much closer to the observed ones than that of mountainous areas. This result comes from the difference of radar rainfall depending on the basin elevation. Therefore we need the examination of radar rainfall transform formulas following rainfall event and runoff analysis based on basin elevation for the improvement of radar rainfall application. Acknowledgment This study was financially supported by the Construction Technology Innovation Program(08-Tech-Inovation-F01) through the Research Center of Flood Defence Technology for Next Generation in Korea Institute of Construction & Transportation Technology Evaluation and Planning(KICTEP) of Ministry of Land, Transport and Maritime Affairs(MLTM)
Chandrasekar, V.; Gorgucci, Eugenio; Scarchilli, Gianfranco
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.
is concerned with the possibility of utilizing weather radar and probabilistic simulation to obtain the rainfall input. Also, the feasibility of a radar, raingage combination is examined. It is shown that quantitative estimates of runoff can be made from...
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...
Radar estimates of rainfall are subject to significant measurement uncertainty. Typically, uncertainties are measured by the discrepancies between area rainfall estimates based on radar reflectivity and point rainfall records of rain gauges. This study investigates how the discrepancies can potent...
Lim, S.; Jang, B. J.; Lee, K. H.; Lee, C.; Kim, W.
As rainfall characteristic is more quixotic and localized, it is important to provide a prompt and accurate warning for public. To monitor localized heavy rainfall, a reliable disaster monitoring system with advanced remote observation technology and high-precision display system is needed. To advance even more accurate weather monitoring using weather radar, there have been growing concerns regarding the real-time changes of mapping radar observations on geographical coordinate systems along with the visualization and display methods of radar data based on spatial interpolation techniques and geographical information system (GIS). Currently, the method of simultaneously displaying GIS and radar data is widely used to synchronize the radar and ground systems accurately, and the method of displaying radar data in the 2D GIS coordinate system has been extensively used as the display method for providing weather information from weather radar. This paper proposes a realistic 3D weather radar data display technique with higher spatiotemporal resolution, which is based on the integration of 3D image processing and GIS interaction. This method is focused on stereoscopic visualization, while conventional radar image display works are based on flat or two-dimensional interpretation. Furthermore, using the proposed technique, the atmospheric change at each moment can be observed three-dimensionally at various geological locations simultaneously. Simulation results indicate that 3D display of weather radar data can be performed in real time. One merit of the proposed technique is that it can provide intuitive understanding of the influence of beam blockage by topography. Through an exact matching each 3D modeled radar beam with 3D GIS map, we can find out the terrain masked areas and accordingly it facilitates the precipitation correction from QPE underestimation caused by ground clutter filtering. It can also be expected that more accurate short-term forecasting will be possible using stereoscopic observation of weather phenomena changes.
Villarini, Gabriele; Seo, Bong-Chul; Serinaldi, Francesco; Krajewski, Witold F.
It is widely acknowledged that radar-based estimates of rainfall are affected by uncertainties (e.g., mis-calibration, beam blockage, anomalous propagation, and ground clutter) which are both systematic and random in nature. Improving the characterization of these errors would yield better understanding and interpretations of results from studies in which these estimates are used as inputs (e.g., hydrologic modeling) or initial conditions (e.g., rainfall forecasting). Building on earlier efforts, the authors apply a data-driven multiplicative model in which the relationship between true rainfall and radar rainfall can be described in terms of the product of a systematic and random component. The systematic component accounts for conditional biases. The conditional bias is approximated by a power-law function. The random component, which represents the random fluctuations remaining after correcting for systematic uncertainties, is characterized in terms of its probability distribution as well as its spatial and temporal dependencies. The space-time dependencies are computed using the non-parametric Kendall's ? measure. For the first time, the authors present a methodology based on conditional copulas to generate ensembles of random error fields with the prescribed marginal probability distribution and spatio-temporal dependencies. The methodology is illustrated using data from Clear Creek, which is a densely instrumented experimental watershed in eastern Iowa. Results are based on three years of radar data from the Davenport Weather Surveillance Radar 88 Doppler (WSR-88D) radar that were processed through the Hydro-NEXRAD system. The spatial and temporal resolutions are 0.5 km and hourly, respectively, and the radar data are complemented by rainfall measurements from 11 rain gages, located within the catchment, which are used to approximate true ground rainfall.
Cao, Qing; Yeary, M. B.; Zhang, Guifu
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…
The Commonwealth Bureau of Meteorology's Weather Watch Radar website provides up-to-date radar images of the locations of rain in Australia in relation to local features such as coast lines. The newly developed Loops provide four consecutive radar images so that users can view how the weather has been changing in the last forty to fifty minutes. The website provides radar images of past cyclone events as well as updates on severe weather throughout Australia. Those interested in radar systems can discover how the weather radars work and how to interpret the maps. [RME
Tanelli, Simone; Im, Eastwood; Durden, Stephen L.
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.
Baeck, M.; Smith, J. A.; Krajewski, W.; Ntelekos, A. A.; Meierdiercks, K.
Analyses of radar rainfall estimates from the WSR-88D radar network are presented for a sample of major flood events in the US. The framework for radar rainfall analysis is the HydroNEXRAD system and analyses highlight the utility of radar rainfall estimates for a diverse range of flood hydrology applications. The sample of flood events focuses on regions of the US with large flood potential, including the Edwards Plateau of Texas, the central Appalachians and urban watersheds of the eastern US. The basin scales of interest range from less than 10 sq. km. to more than 10,000 sq. km. We examine errors in radar rainfall estimates from the perspective of extreme flood-producing storms. Analyses for the Edwards Plateau of Texas focus on major storm events in June 1997 and July 2002. In the Delaware River basin, analyses center on a sequence of record and near-record flood events in September 2003, April 2004 and June 2005.
Habib, M. A.; Habib, E. H.; Vitla, V.
Recent advances in remote sensing of rainfall provide unprecedented opportunities for acquiring rainfall measurements with high spatial and temporal resolutions. In particular, the Next Generation Weather Radar (NEXRAD) system is a promising resource for improving the accuracy and reliability of hydrologic predictions and operational forecasting. However, rainfall estimates from radar measurements are subject to uncertainties caused by both instrumental effects and lack of unique relation between radar-rainfall estimations and the surface rainfall quantities. The effect of such uncertainties on the predictive ability of hydrologic models is an active area of research. This study will investigate the propagation of radar-rainfall estimation uncertainties into the simulation of different rainfall-runoff processes. The analysis is performed over a mid-size watershed that is heavily monitored by a dense network of rainfall and streamflow gauges. The study uses a physically-based distributed hydrological model (Gridded Surface Subsurface Hydrologic Analysis, GSSHA). The model will be calibrated and validated using several historical rainfall-runoff storms. Radar estimation errors will be first assessed in terms of their marginal error distribution and spatial and temporal auto-correlations. Then, radar- based runoff simulations will be assessed in comparison to simulations using data from the dense rain gauge network in the watershed. The study will examine the effect of radar-rainfall uncertainties on simulations of various processes such as infiltration, surface runoff, soil moisture, and streamflow. Then, a simulation-based stochastic model for the radar error will be developed based on its identified characteristics (i.e., marginal distribution and spatio-temporal correlations). This model will provide a tool for generating multiple realizations of the radar error field and enable examination of the probabilistic nature of the error propagation into runoff predictions.
Cifelli, R.; Wang, Y.; Lim, S.; Kennedy, P.; Chandrasekar, V.; Rutledge, S. A.
The efficacy of dual polarimetric radar for quantitative precipitation estimation (QPE) is firmly established. Specifically, rainfall retrievals using combinations of reflectivity (ZH), differential reflectivity (ZDR), and specific differential phase (KDP) have advantages over traditional Z-R methods because more information about the drop size distribution and hydrometeor type are available. In addition, dual-polarization radar measurements are generally less susceptible to error and biases due to the presence of ice in the sampling volume. A number of methods have been developed to estimate rainfall from dual-polarization radar measurements. However, the robustness of these techniques in different precipitation regimes is unknown. Because the National Weather Service (NWS) will soon upgrade the WSR 88-D radar network to dual-polarization capability, it is important to test retrieval algorithms in different meteorological environments in order to better understand the limitations of the different methodologies. An important issue in dual-polarimetric rainfall estimation is determining which method to employ for a given set of polarimetric observables. For example, under what circumstances does differential phase information provide superior rain estimates relative to methods using reflectivity and differential reflectivity? At Colorado State University (CSU), a "blended" algorithm has been developed and used for a number of years to estimate rainfall based on ZH, ZDR, and KDP (Cifelli et al. 2002). The rainfall estimators for each sampling volume are chosen on the basis of fixed thresholds, which maximize the measurement capability of each polarimetric variable and combinations of variables. Tests have shown, however, that the retrieval is sensitive to the calculation of ice fraction in the radar volume via the difference reflectivity (ZDP - Golestani et al. 1989) methodology such that an inappropriate estimator can be selected in situations where radar echo is relatively weak (< 40 dBZ). In this study, a new blended rainfall algorithm is developed using hydrometeor identification (HID) to drive the rainfall estimation algorithm. HID discrimination for rainfall application namely, (1) all rain, (2) mixed precipitation, and (3) all ice, is used to guide the selection of the most appropriate rainfall estimator. Data collected from the CSU-CHILL radar and a network of rain gauges are used to test the performance of the new algorithm in a variety of precipitation situations. The results are compared to similar results using the algorithm from the National Severe Storm Laboratory (NSSL), derived from Oklahoma precipitation events ( Ryzhkov et al. 2005 ). The applicability of the method derived from Oklahoma observations to Colorado precipitation events is also explored.
Marra, Francesco; Nikolopoulos, Efthymios I.; Creutin, Jean-Dominique; Borga, Marco
Identification of rainfall thresholds for the prediction of debris-flow occurrence is a common approach for warning procedures. Traditionally the debris-flow triggering rainfall is derived from the closest available raingauge. However, the spatial and temporal variability of intense rainfall on mountainous areas, where debris flows take place, may lead to large uncertainty in point-based estimates. Nikolopoulos et al. (2014) have shown that this uncertainty translates into a systematic underestimation of the rainfall thresholds, leading to a step degradation of the performances of the rainfall threshold for identification of debris flows occurrence under operational conditions. A potential solution to this limitation lies on use of rainfall estimates from weather radar. Thanks to their high spatial and temporal resolutions, these estimates offer the advantage of providing rainfall information over the actual debris flow location. The aim of this study is to analyze the value of radar precipitation estimations for the identification of debris flow precipitation thresholds. Seven rainfall events that triggered debris flows in the Adige river basin (Eastern Italian Alps) are analyzed using data from a dense raingauge network and a C-Band weather radar. Radar data are elaborated by using a set of correction algorithms specifically developed for weather radar rainfall application in mountainous areas. Rainfall thresholds for the triggering of debris flows are identified in the form of average intensity-duration power law curves using a frequentist approach by using both radar rainfall estimates and raingauge data. Sampling uncertainty associated to the derivation of the thresholds is assessed by using a bootstrap technique (Peruccacci et al. 2012). Results show that radar-based rainfall thresholds are largely exceeding those obtained by using raingauge data. Moreover, the differences between the two thresholds may be related to the spatial characteristics (i.e., spatial variogram) of the triggering rainfall. These results show that weather radar has the potential to effectively increase the accuracy of rainfall thresholds for debris flow occurrence. However, these benefits may only be achieved if the same monitoring instrumentation is used both to derive the rainfall thresholds and for use of thresholds for real-time identification of debris flows occurrence. References Nikolopoulos, E.I., Borga M., Crema S., Marchi L, Marra F. & Guzzetti F., 2014. Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris-flow occurrence. Geomorphology (conditionally accepted) Peruccacci, S., Brunetti, M.T., Luciani, S., Vennari, C., and Guzzetti, F., 2012. Lithological and seasonal control of rainfall thresholds for the possible initiation of landslides in central Italy, Geomorphology, 139-140, 79-90, 2012.
Mazari, N.; Sharif, H. O.; Xie, H.; Tekeli, A. E.; Habib, E. H.; Zeitler, J.
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.
Wang, Li-Pen; Willems, Patrick; Ochoa-Rodriguez, Susana; Onof, Christian
Traditionally, urban hydrological applications relied mainly upon rain gauge data as input as these provide accurate point rainfall estimates near the ground surface. However, they cannot capture the spatial variability of rainfall, which has a significant impact on the urban hydrological system and thus on the modelling of urban pluvial flooding. Thanks to the development of radar technology, weather radar has been playing an increasingly important role in urban hydrology. Radars can survey large areas and better capture the spatial variability of the rainfall, thus improving the short term predictability of rainfall and flooding. However, the accuracy of radar measurements is in general insufficient, particularly in the case of extreme rainfall magnitudes. This has a tremendous effect on the subsequent hydraulic model outputs. In order to improve the accuracy of radar rainfall estimates while preserving their spatial description of rainfall fields, it is possible to dynamically adjust them based on rain gauge measurements. Studies on this subject have been carried out over the last few years, though most of them focus on the hydrological applications at large scales. A couple of recent research works have examined the applicability of these adjustment techniques to urban-scale hydrological applications and concluded that these techniques can effectively reduce rainfall bias, thus leading to improvements in the reproduction of hydraulic outputs (Wang et al., 2013). However, underestimation of storm peaks can still be seen after adjustment and this is particularly significant in the case of small drainage areas and for extreme rainfall magnitudes. This may be due to the fact that the underlying adjustment techniques, mainly based upon Gaussian approximations, cannot properly cope with the non-normality observed in urban scale applications. With the purpose of improving this aspect, a methodology has been developed which identifies the local extremes or 'singularities' of radar rainfall fields and preserves them throughout the merging process (Wang and Onof, 2013). Singularities are defined through the fact that the areal average rainfall increases as a power function when the area decreases (Cheng et al., 1994). In the proposed methodology singularities are first identified and extracted from the radar rainfall field. The resulting non-singular radar field is then used in the merging process and the singularities are subsequently and proportionally added back to the final reconstructed rainfall field. A full-scale testing of this methodology in an urban area in the UK has been conducted and the result suggests that the original Bayesian data merging technique (Todini, 2001) could be effectively improved by incorporating this singularity analysis. References Cheng, Q., et al., (1994) Journal of Geochemical Exploration, 51(2), 109-130. Todini, E., (2001) Hydrology and Earth System Sciences, 5, 187-199. Wang, L. et al., (2013) Water Science & Technology, 68(4), 737-747. Wang, L. and Onof, C., (2013) Hydrofractals '13, Kos island, Greece.
Yu, P.; Chou, J.; Chiu, Y.; Yang, T.; Kuo, C.
This study aims to establish a flood prediction model in Dajia River by using a grid-based distributed rainfall-runoff model (GDRRM) combined with the predicted QPESUMS radar rainfalls. Flood disasters caused damage to human and property. A proper flood prediction model can provide warning messages against disasters. Since the radar rainfall technology has been developed for years, it has the ability to represent the precipitation in each location. Coupling the real-time radar rainfall with the distributed rainfall-runoff model, it can be used to provide the probable flow in downstream. The study area, Dajia River basin, is located in central Taiwan. The river flow is mainly controlled by two major reservoirs, Shih-Kang Dam in downstream and Te-Chi Reservoir in upstream. Thus, three components are considered for establishing the flood prediction model. The first one is the application of radar rainfalls. The real-time and predicted (1-3hr ahead) radar rainfall data provided by the Central Weather Bureau, Taiwan were set as the input data. It can represent the actual distributed rainfalls of the basin. The second one is the estimation of reservoir inflow by using a GDRRM. The basin was divided into 1234 regular grids (1km by 1km) to exhibit the heterogeneity in the watershed. The parameters of GDRRM were generated by using DEM, Formosat-2 satellite image and soil map to represent the actual geography and physiography of each grid. With the input of real-time and predicted radar rainfall data, the inflow of Te-Chi Reservoir and Shih-Kang Dam can be calculated by using two GDRRMs respectively. The third one is the operation rules of reservoir used for simulating the outflow of the reservoirs during the flow simulation. Then, the downstream (Shih-Kang Dam) GDRRM coupled with the operation rules was used to calculate the outflow of the Te-Chi Reservoir. Thus, the flood can be predicted in advance during typhoon period. The results revealed that the flood prediction model has good performances in simulating the outflows of seven historical typhoon events. With the proposed flood prediction model, it can be coupled with flow routing and sediment transport models to develop a warning system for bridge damage in downstream of Dajia River.
Influence of small scale rainfall variability on standard comparison tools between radar and rain in revised form 18 October 2013 Accepted 8 November 2013 Rain gauges and weather radars do not measure), and one of 16 rain gauges (Bradford, United Kingdom) both located within a 1 km2 area. Second
Liu, J.; Bray, M.; Han, D.
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 evaluated by examining the rainfall temporal variations and total amounts which have direct impacts on rainfall-runoff transformation in hydrological applications. It is found that by solely assimilating radar data, the improvement of rainfall forecasts are not as obvious as assimilating meteorological data; whereas the positive effect of radar data can be seen when combined with the traditional meteorological data, which leads to the best rainfall forecasts among the five modes. To further improve the effect of radar data assimilation, limitations of the radar correction ratio developed in this study are discussed and suggestions are made on more efficient utilisation of radar data in NWP data assimilation.
Meneghini, R.; Bidwell, S.; Liao, L.; Rincon, R.; Heymsfield, G.; Hildebrand, Peter H. (Technical Monitor)
The Precipitation Radar aboard the Tropical Rain Measuring Mission (TRMM) Satellite has shown the potential for spaceborne sensing of snow and rain by means of an incoherent pulsed radar operating at 13.8 GHz. The primary advantage of radar relative to passive instruments arises from the fact that the radar can image the 3-dimensional structure of storms. As a consequence, the radar data can be used to determine the vertical rain structure, rain type (convective/stratiform) effective storm height, and location of the melting layer. The radar, moreover, can be used to detect snow and improve the estimation of rain rate over land. To move toward spaceborne weather radars that can be deployed routinely as part of an instrument set consisting of passive and active sensors will require the development of less expensive, lighter-weight radars that consume less power. At the same time, the addition of a second frequency and an upgrade to Doppler capability are features that are needed to retrieve information on the characteristics of the drop size distribution, vertical air motion and storm dynamics. One approach to the problem is to use a single broad-band transmitter-receiver and antenna where two narrow-band frequencies are spaced apart by 5% to 10% of the center frequency. Use of Ka-band frequencies (26.5 GHz - 40 GHz) affords two advantages: adequate spatial resolution can be attained with a relatively small antenna and the differential reflectivity and mean Doppler signals are directly related to the median mass diameter of the snow and raindrop size distributions. The differential mean Doppler signal has the additional property that this quantity depends only on that part of the radial speed of the hydrometeors that is drop-size dependent. In principle, the mean and differential mean Doppler from a near-nadir viewing radar can be used to retrieve vertical air motion as well as the total mean radial velocity. In the paper, we present theoretical calculations for the differential reflectivity and Doppler as functions of the center frequency, frequency difference, and median mass diameter. For a fixed pair of frequencies, the detectability of the differential signals can be expressed as the number of independent samples required to detect rain or snow with a particular median mass diameter. Because sampling numbers on the order of 1000 are needed to detect the differential signal over a range of size distributions, the instrument must be confined to a near-nadir, narrow swath. Radar measurements from a zenith directed radar operated at 9.1 GHz and 10 GHz are used to investigate the qualitative characteristics of the differential signals. Disdrometer and rain gauge data taken at the surface, just below the radar, are used to test whether the differential signals can be used to estimate characteristics of the raindrop size distribution.
Nanding, Nergui; Rico-Ramirez, Miguel Angel; Han, Dawei
Rainfall estimates by weather radar have become an important alternative to raingauge measurements for hydrological modelling over poorly gauged catchments, due to its capability for providing spatially distributed rainfall with a high resolution in space and time. However, the potential of radar rainfall estimates has often been limited by a variety of source of errors. More recently, research has proven that by combining radar rainfall estimates with raingauge measurements it is possible to obtain better rainfall estimates that are also able to capture the spatial precipitation variability. However, the impact of using merged rainfall products as compared with conventional raingauge inputs, with respect to various hydrological model structures and catchment areas, remains unclear and yet to be addressed. In the study presented by this paper, we analysed the flow simulations of different sized catchments across Northern England using rainfall inputs from different radar-raingauge merging techniques, such as Kriging with radar-based correction (KRE) and Kriging with external drift (KED). Rainfall was estimated at an hourly timescale and therefore rainfall estimates obtained from different radar-gauge merging techniques at hourly resolution are incorporated into hydrological models so that direct comparison of streamflows can be explored. The main purpose of this paper is to examine whether these merged rainfall estimates are useful as input to rainfall-runoff models over rural catchment areas, focusing on the improvement of rainfall estimates by radar-raingauge merging techniques for runoff predictions rather than on the rainfall estimates themselves in relation to the catchments sizes and storm events.
...2010-01-01 2010-01-01 false Airborne weather radar equipment requirements. 125...Requirements § 125.223 Airborne weather radar equipment requirements. (a...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2010-01-01 2010-01-01 false Airborne weather radar equipment requirements. 121...Requirements § 121.357 Airborne weather radar equipment requirements. ...December 31, 1964, unless approved airborne weather radar equipment has been installed...
...2010-01-01 2010-01-01 false Airborne weather radar equipment requirements. 135...and Equipment § 135.175 Airborne weather radar equipment requirements. ...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2013-01-01 2013-01-01 false Airborne weather radar equipment requirements. 135...and Equipment § 135.175 Airborne weather radar equipment requirements. ...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2012-01-01 2012-01-01 false Airborne weather radar equipment requirements. 135...and Equipment § 135.175 Airborne weather radar equipment requirements. ...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2012-01-01 2012-01-01 false Airborne weather radar equipment requirements. 121...Requirements § 121.357 Airborne weather radar equipment requirements. ...December 31, 1964, unless approved airborne weather radar equipment has been installed...
...2013-01-01 2013-01-01 false Airborne weather radar equipment requirements. 125...Requirements § 125.223 Airborne weather radar equipment requirements. (a...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2011-01-01 2011-01-01 false Airborne weather radar equipment requirements. 121...Requirements § 121.357 Airborne weather radar equipment requirements. ...December 31, 1964, unless approved airborne weather radar equipment has been installed...
...2014-01-01 2014-01-01 false Airborne weather radar equipment requirements. 135...and Equipment § 135.175 Airborne weather radar equipment requirements. ...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2014-01-01 2014-01-01 false Airborne weather radar equipment requirements. 125...Requirements § 125.223 Airborne weather radar equipment requirements. (a...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2014-01-01 2014-01-01 false Airborne weather radar equipment requirements. 121...Requirements § 121.357 Airborne weather radar equipment requirements. ...December 31, 1964, unless approved airborne weather radar equipment has been installed...
...2013-01-01 2013-01-01 false Airborne weather radar equipment requirements. 121...Requirements § 121.357 Airborne weather radar equipment requirements. ...December 31, 1964, unless approved airborne weather radar equipment has been installed...
...2011-01-01 2011-01-01 false Airborne weather radar equipment requirements. 125...Requirements § 125.223 Airborne weather radar equipment requirements. (a...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2011-01-01 2011-01-01 false Airborne weather radar equipment requirements. 135...and Equipment § 135.175 Airborne weather radar equipment requirements. ...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
...2012-01-01 2012-01-01 false Airborne weather radar equipment requirements. 125...Requirements § 125.223 Airborne weather radar equipment requirements. (a...passenger-carrying operations unless approved airborne weather radar equipment is installed in the...
Modeling Radar Rainfall Estimation Uncertainties: Random Error Model A. AghaKouchak1 ; E. Habib2 ; and A. Bárdossy3 Abstract: Precipitation is a major input in hydrological models. Radar rainfall data compared with rain gauge measurements provide higher spatial and temporal resolutions. However, radar data
Liu, Xinan; Zheng, Quanan; Liu, Ren; Duncan, James H.
A model of radar backscattering from the ocean surface in response to rainfall is developed. The model shows that the radar return intensity is a function of the wavelength and incident angle of the radar waves and the rain rate. The model explains the differences between the radar response to rain rate simultaneously observed by C-band ASAR and ground-based weather radar. An experiment on the simultaneous measurements of the characteristics of the ocean surface in response to rainfall and its radar back-scatter is performed in the laboratory. The experiment is carried out in a water pool that is 1.22 m by 1.22 m with a water depth of 0.3 m. Artificial rainfall is generated from an array of hypodermic needles. The surface characteristics including crowns, stalks and ring waves are measured with a cinematic Laser-Induced-Florescence (LIF) technique while secondary droplets are measured with a shadowgraph technique. The radar backscattering signal is recorded with a dual-polarized, ultra-wide band radar. The frequency dependence and polarization of the radar signatures due to the surface features are discussed. A model of radar backscattering from the ocean surface in response to rainfall is developed. The model shows that the radar return intensity is a function of the wavelength and incident angle of the radar waves and the rain rate. The model explains the differences between the radar response to rain rate simultaneously observed by C-band ASAR and ground-based weather radar. An experiment on the simultaneous measurements of the characteristics of the ocean surface in response to rainfall and its radar back-scatter is performed in the laboratory. The experiment is carried out in a water pool that is 1.22 m by 1.22 m with a water depth of 0.3 m. Artificial rainfall is generated from an array of hypodermic needles. The surface characteristics including crowns, stalks and ring waves are measured with a cinematic Laser-Induced-Florescence (LIF) technique while secondary droplets are measured with a shadowgraph technique. The radar backscattering signal is recorded with a dual-polarized, ultra-wide band radar. The frequency dependence and polarization of the radar signatures due to the surface features are discussed. The work is supported by National Science Foundations, Division of Ocean Science.
Mishra, K. V.; Kruger, A.; Krajewski, W. F.; Xu, W.
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.
Witold F. Krajewski; R. Raghavan; V. Chandrasekar
A scheme for simulating radar-estimated rainfall fields is described. The scheme uses a two-dimensional stochastic space time model of rainfall events and a parameterization of drop-size distribution. Based on the statistically generated drop-size distribution, radar observables, namely, radar reflectivity and differential reflectivity, are calculated. The simulated measurable variables are corrupted with random measurement error to account for radar measurement process.
Rojas, Laura; Nordling, Kalle; Cremonini, Roberto; Moisseev, Dmitri; Chandrasekar, Venkatachalam
High resolution precipitation data is a crucial factor for hydrological applications in urban areas. Small fluctuations in precipitation fields are of great importance considering the fast response of urban catchments due to the dominance of impervious surfaces. High resolution precipitation observations are needed in order to characterize these fluctuations. Weather radar provides high spatial resolution precipitation estimations. However, the quality of its observations in an urban environment is significantly degraded, among other things, by ground clutter and beam-blockage. A solution for this problem is to use a radar network, where the data gaps of one radar will be filled by using observations from the others. Very few cities have dedicated weather radar networks. In some cities, like Helsinki, there are several weather radars covering the metropolitan area, but they are operated by different organizations. In this study, we show how such systems can be used to build a network and what is the advantage of using radarnetworks for estimating precipitation in urban catchments. The urban Helsinki area is covered by observations from three individual-purpose C-band weather radars (Helsinki University's Kumpula (KUM), Vaisala Oy's Kerava (KER) and Finnish Meteorological Institute's Vantaa (VAN)). We used the data from these radars to form a network and we design a similar task which runs at the same time in each radar couple of times per day. Nonetheless, it is challenging to make them observe at the same area at exactly the same time, which could lead to fast changing, short precipitation events being missed. Hence, synchronization and temporal resolution are the main concerns when building a network. Consequently, to decrease the impact of these restrictions in the Helsinki radar network we propose the use of the optic flow interpolation algorithm to retrieve information in between two radar observations and use the retrieved dataset from the three radars to estimate rainfall. The accuracy of this method is studied by comparing the composite rainfall estimation with both single radar observations and ground measurements.
Heimann, Marian; Straub, Daniel; Mok, Chin Man Bill
Accurate representation of the spatial and temporal distribution of rainfall intensity is crucial to development of robust calibrated hydrologic models. Rainfall data are commonly collected using rain gauges and Doppler radar. Rain gauge data are more accurate but they only yield information at point locations. Radar data provide continuous spatial information but they are less accurate. We present a Bayesian approach for integrating gauge and radar data to develop more accurate and continuous rainfall interpretation. In a Bayesian framework, the resulting probability distribution of rainfall intensity (posterior distribution) at a location at a time step is computed from a prior distribution and a likelihood function. Here, the prior distribution is estimated from the rain gauge data by applying geostatistical methods. The likelihood function is calculated based on the mismatch errors between the rainfall radar and rainfall gauge data where they overlap. We shortly discuss an earlier applied model based on a lognorm-transform of a Gaussian random field, but then focus on a novel non-parameteric approach. Therein, at each time step, a range of rainfall threshold levels is considered. For each threshold level, rain gauge and radar data are encoded into indicator values with 1 denoting rainfall intensity greater than the threshold level, 0 otherwise. Radar data are used to characterize the correlation structure of the indicator field. We study and compare several characterization approaches. Indicator Kriging using the resulting correlation model is applied to gauge indicator data to compute the prior estimate of the probability of exceeding the rainfall threshold. A fault table based on comparison of gauge and radar indicator values is used to compute the likelihood at each location. The resulting posterior estimate of the probability of exceeding the rainfall threshold is equal to the value of the posterior cumulative probability distribution function value. We applied this Bayesian approach to the gauge and radar rainfall data collected between January 1, 1995 to June 30, 2003 in the Tampa Bay region in Florida, US. The inconsistency between the radar rainfall estimation and rain gauge point measurements were evaluated. Results show that Bayesian Integration of radar rainfall with rain gauge measurements using the proposed non-parametric threshold approach holds the potential to improve rainfall estimations. Posterior rainfall estimations obtained from Bayesian Integration show higher accuracy than rainfall estimations obtained from Kriging along and are consistent with all rain gauge data. We also have experimented with a Bayesian Integration based on the lognorm-transform of a Gaussian approach. Although the log-transformation approach is computationally more efficient than the proposed non-parametric approach, it can lead to unrealistically large rainfall. The non-parametric approach does not have this problem.
Kubo, Osamu; Kobayashi, Yasuhiro
Weather derivatives are getting to be powerful tools for weather risk hedging. A popular method which draws out valid prices of weather derivatives is a stochastic modeling approach. In the method, expected payoffs of weather derivatives based on stochastic weather models are regarded as their valid prices. Although useful stochastic models of temperature have been shown, stochastic models of daily rainfall are still being developed. Therefore, it is considered that pricing of daily rainfall derivatives is difficult. This paper shows a new stochastic daily rainfall model for pricing daily rainfall options. The new model in which a modified geometric distribution model is applied can express stochastic features of daily rainfall. Furthermore, this paper also shows that the combination model of the Markov chain rainy day model and the new model can express stochastic features and risks of daily rainfall option payoffs.
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 short-term predictability of precipitation patterns depicted by high-resolution reflectivity data observed at microalpha (0.2--2 km) to mesobeta (20--200 km) scales by the CASA radar network. Additionally, DARTS was used to investigate the performance of nowcasting rainfall fields derived from specific differential phase estimates, which have been shown to provide more accurate and robust rainfall estimates compared to those made from radar reflectivity data.
Reich, Brian J.
fields. Doppler radar data offer better spatial and temporal coverage, but Doppler radar measuresSpatial-temporal mesoscale modelling of rainfall intensity using gage and radar data Montserrat effective radar reflectivity (Ze) rather than rainfall rate (R). Thus, rainfall estimates from radar data
Zdenek, David James
DIFFERENCES IN RADAR DERIVED RAINFALL AMOUNTS DUE TO SAMPLING INTERVALS A Thesis by DAVID JAMES ZDENEK Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements for the degree of MASTER OF SCIENCE... December 1986 Major Subject: Meteorology DIFFERENCES IN RADAR DERIVED RAINFALL AMOUNTS DUE TO SAMPLING INTERVALS A Thesis by DAVID JAMES ZDENEK Approved as to style and content by: eorge L. Huebner (Chairman of Committee) CP~ CG~& Robert C...
Fornear, Jeffrey Lynn
SAMPLING-RATE EFFECTS ON RADAR-DERIVED RAINFALL ESTIMATES A Thesis by JEFFREY LYNN FORNEAR Submitted to the Graduate College of Texas APM University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE August 1985... Major Subject: Meteorology SAMPLING-RATE EFFECTS ON RADAR-DERIVED RAINFALL ESTIMATES A Thesis by JEFFREY LYNN FORNEAR Approved as to style and content by: G rge L. uebner (Chairman of Committee) Rudo ph J. Freund ( ember) Robert C. Runnels...
in the European Weather Radar Network. The third phase of the OPERA program is a joint effort of 28 European the Program as the host of the European Weather Radar Network. 2 Layout of the Program Since 1 January 2007The European Weather Radar Network (OPERA): An opportunity for hydrology! Iwan Holleman1 , Laurent
Wang, Li-Pen; Ochoa-Rodriguez, Susana; Onof, Christian; Willems, Patrick
Radar rainfall estimates are playing an increasingly important role in urban hydrological applications due to their better description of the spatial and temporal characteristics of rainfall. However, the operational radar rainfall products provided by national weather services (typically at 1 km / 5 min resolution) still fail to meet the stringent resolution requirements of urban hydrological applications. While the spatial and temporal resolution of rainfall inputs are strongly related, recent studies suggest that the latter generally constitutes a more critical factor and that temporal resolutions of ~1-2 min (i.e. below those currently available) are required for urban hydrological applications, while spatial resolutions of ~1 km (i.e. close to those currently available) appear to be sufficient. Traditional strategies for obtaining higher temporal resolution radar rainfall estimates include changes in radar scanning strategies and stochastic downscaling. However, the former is not always possible, due to hardware limitations, and the latter results in large ensembles members which hinder practical use. In this work a temporal interpolation method, based upon the multi-scale variational optical flow technique, is proposed to generate high temporal-resolution (i.e. 1-2 min) radar rainfall estimates. The proposed method has been successfully applied to obtain radar rainfall estimates at 1 and 2 min temporal resolutions from UK Met Office C-band radar products originally at 5 and 10 min temporal resolution and varying spatial resolutions of 1 km, 500 m and 100 m. The performance of the higher temporal-resolution radar rainfall estimates was assessed through comparison against local rain gauge records collected at a pilot urban catchment (size ~ 865 ha) in North-East London. A further evaluation was conducted by applying the different rainfall products as input to the hydraulic model of the pilot catchment and comparing the hydraulic outputs against available flow and depth records. The results show that the temporally-interpolated rainfall estimates can better reproduce the small-scale dynamics of the storm events, leading to better reproduction of urban runoff.
Liu, Xinan; Zheng, Quanan; Liu, Ren; Duncan, James H.
The characteristics of ocean surface in response to rainfall and its radar back-scatter are simultaneously measured in laboratory. The experiment is carried out in a water pool that is 1.22 m by 1.22 m with a water depth of 0.3 m. Artificial rainfall is generated from an array of hypodermic needles. The surface characteristics including crowns, stalks, secondary droplets and ring waves are measured with a cinematic Laser-Induced-Florescence (LIF) technique. Our experimental results show that impinging raindrops on the water surface generate various water surface structures with different relative sizes. Among them stalks and crowns comprise the dominant radar backscattering. On the basis of these laboratory experiments and theories of radar scattering from a rough surface, a near-resonance radar backscattering model for quantifying the dependence of the radar return intensity on rain rate on the ocean surface is developed. The model explains the radar response to rain rate simultaneously observed by C-band ASAR and ground-based weather radar. The physical model provides reasonable mechanisms to explain the frequency dependence and polarization behavior of radar signatures from rain cells on the ocean surface. This work is supported by the National Science Foundation, Division of Ocean Sciences under grant OCE962107.
Cummings, R. J.; Upton, G. J. G.; Holt, A. R.; Kitchen, M.
The final stage in processing radar data so as to arrive at an estimated rain field typically involves a comparison of the preliminary radar-derived estimates of hourly rainfall with those observed by ground-based gauges. Often a mean field bias adjustment will then be applied using an age-weighted average of the individual gauge-radar comparisons. In this paper, a mean field bias adjustment is presented that uses the path-integrated rainfall estimates provided by microwave links together with information from gauges. It is shown to be at least as efficient as the current gauge-based procedure used by the UK Met Office to improve the accuracy of radar-based estimates of rainfall at the ground.
Heistermann, M.; Pfaff, Th.; Jacobi, S.
Weather radar data is potentially useful in meteorology, hydrology, disaster prevention and mitigation. Its ability to provide information on precipitation with high spatial and temporal resolution over large areas makes it an invaluable tool for short term weather forecasting or flash flood forecasting. The indirect method of measuring the precipitation field, however, leads to a significant number of data artifacts, which usually must be removed or dealt with before the data can be used with acceptable quality. Data processing requires e.g. the transformation of measurements from polar to cartesian coordinates and from reflectivity to rainfall intensity, the composition of data from several radar sites in a common grid, clutter identification and removal, attenuation and VPR corrections, gauge adjustment and visualization. The complexity of these processing steps is a major obstacle for many potential users in science and practice. Adequate tools are available either only at significant costs with no access to the uncerlying source code, or they are incomplete, insufficiently documented and intransparent. The wradlib project has been initiated in order to lower the barrier for potential users of weather radar data in the geosciences and to provide a common platform for research on new algorithms. wradlib is an open source library for the full range of weather radar related processing algorithms, which is well documented and easy to use. The main parts of the library are currently implemented in the python programming language. Python is well known both for its ease of use as well as its ability to integrate code written in other programming languages like Fortran or C/C++. The well established Numpy and Scipy packages are used to provide decent performance for pure Python implementations of algorithms. We welcome contributions written in any computer language and will try to make them accessible from Python. We would like to present the current state of this library together with a few showcase examples.
Seo, Bong-Chul; Cunha, Luciana K.; Krajewski, Witold F.
This study addresses a significant potential source of error that exists in radar-rainfall maps that are combined using data from multiple WSR-88D radars of the Next Generation Radar (NEXRAD) national network in the United States. This error stems from different radar calibration offsets that create a border within discontinuous rainfall fields at the equidistance zone among radars. The discontinuity in rainfall fields could lead to misestimation of rainfall over basins and subsequently, to significant errors in streamflow predictions through a hydrologic model. In this study, we produce enhanced radar-rainfall estimates (HN3) based on a novel approach that allows us to reduce the effects of the relative radar calibration bias. We use the relative bias information previously presented in a radar reflectivity comparison study. To investigate the effects of the relative bias adjustment, we evaluate the HN3 and Stage IV radar-rainfall by comparing them with rain gauge data and analyzing their ability to simulate streamflow for an extreme flood case. While the HN3 estimates are statistically comparable to the Stage IV estimates in the rain gauge data comparison, the borderline that identifies discontinuous rainfall fields disappears in the HN3 estimates. We performed hydrological simulations using a physically based, data-intensive, calibration-free, hillslope-link hydrologic model called CUENCAS and demonstrated CUENCAS's ability to accurately simulate flows by comparing results with observed and predicted streamflow generated by the Sacramento (SAC) model. SAC is the operational flood forecast model that has been used by the National Weather Service since 1969, and it was extensively calibrated based on historical data. The simulation results show that the adjustment improves streamflow predictions in the regions where the misestimation of rainfall quantity is considerable. We conclude that systematic error arising from different calibration offsets in rainfall fields can significantly affect hydrologic predictions.
Marks, D. A.; Wolff, D. B.
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 weather systems.
Villarini, G.; Seo, B.; Serinaldi, F.; Krajewski, W. F.
It is well acknowledged that radar-based estimates of rainfall are affected by several sources of uncertainties (e.g., mis-calibration, beam blockage, anomalous propagation and ground clutter), which are both systematic and random in nature. Improved characterization of these errors would result in our improved understanding and interpretation of the results from those studies in which these estimates are used as input (e.g., hydrologic modeling) or initial condition (e.g., rainfall forecasting). Building on earlier efforts, the authors apply a data-driven multiplicative model, in which the relation between true rainfall and radar rainfall can be described in terms of the product of a systematic and a random component. The systematic components accounts for both unconditional and conditional biases. The conditional bias is parameterized by a power-law function. The random component, which represents the random fluctuations remaining after correcting for systematic uncertainties, is characterized in terms of its probability distribution, and spatial and temporal dependencies. The space-time dependencies are computed using the non-parametric Kendall's tau measure. The authors present a methodology based on dynamic copulas to generate ensembles of random error fields with the prescribed spatial and temporal dependencies. They discuss application of this model to flash flood forecasting. The focus area of this study is Clear Creek, which is a densely instrumented experimental watershed in eastern Iowa Results are based on about three years of radar data from the Davenport Weather Surveillance Radar 88 Doppler (WSR-88D) radar, and processed through the Hydro-NEXRAD system. The spatial and temporal resolutions are 0.5 km and hourly. The radar data are complemented by rainfall measurements from 11 rain gages located within the catchment, which are used as an approximation of the true ground rainfall.
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. ...
Jameson, Arthur R.
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.
Pessoa, M.L.; Bras, R.L.; Williams, E.R. (Massachusetts Inst. of Technology, Cambridge (United States))
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.
Seo, Bong-Chul; Krajewski, Witold; Cunha, Luciana; Dolan, Brenda; Smith, James; Rutledge, Steven; Petersen, Walter
Rainfall products estimated using ground-based radars are often used as reference to assess capabilities and limitations of using satellite rainfall estimates in hydrologic modeling and prediction. During the spring of 2013, NASA conducted a hydrology-oriented field campaign called Iowa Flood Studies (IFloodS) in the central and northeastern Iowa in the United States, as a part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission. The purpose of IFloodS was to enhance the understanding of flood-related rainfall processes and the predictability in flood forecasting. While there are multiple types of rainfall data sets (e.g., satellite, radar, rain gauge, and disdrometer) available as the observational assets of IFloodS, the authors focus on the evaluation of multi-scale rainfall products observed from ground-based radars. The radar-only products used in the evaluation are the NEXRAD single polarization products (i.e., Stage IV, NMQ Q2, and Iowa Flood Center rainfall maps) and products generated using dual-polarization procedures (i.e., the U.S. National Weather Service operational and Colorado State University experimental blended precipitation processing algorithms) with comparable space and time resolution. The NASA NPOL S-band radar products are also evaluated and compared with the aforementioned NEXRAD products. The uncertainty for different temporal and spatial resolution products is characterized using ground reference data of dense rain gauge and disdrometer networks. This multi-scale characterization is required for hydrologic modeling frameworks that assess model predictive abilities as a function of space and time scales.
Hu, Zhiqun; Liu, Liping; Wang, Lirong
A mobile C-band dual polarimetric weather radar J type (PCDJ), which adopts simultaneous transmission and simultaneous reception (STSR) of horizontally and vertically polarized signals, was first developed in China in 2008. It was deployed in the radar observation plan in the South China Heavy Rainfall Experiment (SCHeREX) in the summer of 2008 and 2009, as well as in Tropical Western Pacific Ocean Observation Experiments and Research on the Predictability of High Impact Weather Events from 2008 to 2010 in China (TWPOR). Using the observation data collected in these experiments, the radar systematic error and its sources were analyzed in depth. Meanwhile an algorithm that can smooth differential propagation phase ( ? DP) for estimating the high-resolution specific differential phase ( K DP) was developed. After attenuation correction of reflectivity in horizontal polarization ( Z H) and differential reflectivity ( Z DR) of PCDJ radar by means of K DP, the data quality was improved significantly. Using quality-controlled radar data, quantitative rainfall estimation was performed, and the resutls were compared with rain-gauge measurements. A synthetic Z H / K DP-based method was analyzed. The results suggest that the synthetic method has the advantage over the traditional Z H-based method when the rain rate is >5 mm h-1. The more intensive the rain rates, the higher accuracy of the estimation.
As long recognized, one of the primary sources of the discrepancies in the radar-based rainfall estimates and rain gauge measurements is the point-area difference, i.e., the intrinsic difference in the spatial dimensions of the rainfall fields that radar rainfall estimates and gauge measurements are...
Liguori, Sara; Rico-Ramirez, Miguel
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 , has been developed for the purpose of this work. An ensemble generator has been calibrated on the basis of the spatial-temporal characteristics of the residual error in radar estimates assessed with reference to rainfall records from around 200 rain gauges available for the year 2007, previously post-processed and corrected by the UK Met Office [12-13]. Each ensemble member is determined by summing a perturbation field to the unperturbed radar rainfall field. The perturbations are generated by imposing the radar error spatial and temporal correlation structure to purely stochastic fields. A hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water . The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References  Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003  Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129.  Villarini G, Krajewski WF, 2010. Review of the different sources of uncertainty in single polarization radar-based estimate
Hasan, M. M.; Sharma, A.; Johnson, F.; Mariethoz, G.; Seed, A.
Accurate estimation of rainfall is critical for any hydrological analysis. The advantage of radar rainfall measurements is their ability to cover large areas. However, the uncertainties in the parameters of the power law, that links reflectivity to rainfall intensity, have to date precluded the widespread use of radars for quantitative rainfall estimates for hydrological studies. There is therefore considerable interest in methods that can combine the strengths of radar and gauge measurements by merging the two data sources. In this work, we propose two new developments to advance this area of research. The first contribution is a non-parametric radar rainfall estimation method (NPZR) which is based on kernel density estimation. Instead of using a traditional Z-R relationship, the NPZR accounts for the uncertainty in the relationship between reflectivity and rainfall intensity. More importantly, this uncertainty can vary for different values of reflectivity. The NPZR method reduces the Mean Square Error (MSE) of the estimated rainfall by 16 % compared to a traditionally fitted Z-R relation. Rainfall estimates are improved at 90% of the gauge locations when the method is applied to the densely gauged Sydney Terrey Hills radar region. A copula based spatial interpolation method (SIR) is used to estimate rainfall from gauge observations at the radar pixel locations. The gauge-based SIR estimates have low uncertainty in areas with good gauge density, whilst the NPZR method provides more reliable rainfall estimates than the SIR method, particularly in the areas of low gauge density. The second contribution of the work is to merge the radar rainfall field with spatially interpolated gauge rainfall estimates. The two rainfall fields are combined using a temporally and spatially varying weighting scheme that can account for the strengths of each method. The weight for each time period at each location is calculated based on the expected estimation error of each method, leading to a dynamic weighting scheme. The weighted combination method reduces the MSE by close to 50% compared to a traditional power law method for using the radar reflectivity. The combined method has the lowest overall error of the three methods over the densely gauged Sydney region.
This resource is intended for use as a job aid by operational weather forecasters in live warning situations and as a reference tool to better understand some aspects of severe thunderstorm warning events. Thumbnail images show typical representatives for sixteen radar reflectivity and velocity signatures as well as three primary severe storm types. Each signature links to content describing detection techniques and conceptual and diagnostic information to help determine storm severity. The majority of the examples shown are southern hemisphere storms in Australia; examples from the northern hemisphere are noted.
Weinman, J. A.; Meneghini, R.; Nakamura, K.
Precipitation profiles retrieved from a dual frequency X- and Ka-band radar and from an X-band radiometer are analyzed. Profiles from combined radar and microwave radiometer measurements are compared to those from dual frequency radar measurements to study the performance of the combined radar-radiometer retrievals. A method for the retrieval of rainfall rate profiles from attenuated radar returns and passive radiometric data is presented. The results suggest that the operation of a single frequency radar with multifrequency passive radiometers may provide cost-effective spaceborne measurements of global tropical rainfall distributions. The possible use of this methodology for the Tropical Rainfall Measuring Mission is considered.
Heinonen, M; Jokelainen, M; Fred, T; Koistinen, J; Hohti, H
Municipal wastewater treatment plant (WWTP) influent is typically dependent on diurnal variation of urban production of liquid waste, infiltration of stormwater runoff and groundwater infiltration. During wet weather conditions the infiltration phenomenon typically increases the risk of overflows in the sewer system as well as the risk of having to bypass the WWTP. Combined sewer infrastructure multiplies the role of rainwater runoff in the total influent. Due to climate change, rain intensity and magnitude is tending to rise as well, which can already be observed in the normal operation of WWTPs. Bypass control can be improved if the WWTP is prepared for the increase of influent, especially if there is some storage capacity prior to the treatment plant. One option for this bypass control is utilisation of on-line weather-radar-based forecast data of rainfall as an input for the on-line influent model. This paper reports the Viikinmäki WWTP wet weather influent modelling project results where gridded exceedance probabilities of hourly rainfall accumulations for the next 3 h from the Finnish Meteorological Institute are utilised as on-line input data for the influent model. PMID:23925175
Chandrasekar, V.; Bringi, V. N.
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.
Bush, Susan M.
An operational demonstration of Terminal Doppler Weather Radar (TDWR) at Stapleton International Airport, Denver, finishes August 31. For 2 months, TDWR has been used to detect wind shear and other hazardous weather around air terminals and to provide warnings to air traffic controllers and pilots in time to avert accidents.The biggest hazard for aircraft approaching or departing terminals is the microburst, a form of wind shear. Microbursts are produced by a small-scale, powerful downdraft of cold, heavy air occurring beneath a thunderstorm, rain shower, or cumulus cloud. As the downdraft reaches Earth's surface, it spreads out horizontally (see Figure 1). An aircraft flying through a microburst at low-altitude encounters a strong headwind, then a downdraft, and finally a tailwind that causes a sharp reduction in speed and loss of lift. This deadly sequence of events has caused at least 30 accidents and 500 deaths in the United States since the mid-1960s.
Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Schellart, Alma; Berne, Alexis; Lovejoy, Shaun
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.
Dai, Qiang; Han, Dawei
Due to the fact that weather radar is prone to several sources of errors, it is acknowledged that adjustment against ground observations such as rain gauges is crucial for radar measurement. Spatial matching of precipitation patterns between radar and rain gauge is a significant premise in radar bias corrections. It is a conventional way to construct radar-gauge pairs based on their vertical locations. However, due to the wind effects, the raindrops observed by the radar do not always fall vertically to the ground, and the raindrops arriving at the ground may not all be caught by the rain gauge. This study proposes a fully formulated scheme to numerically simulate the movement of raindrops in a three-dimensional wind field in order to adjust the wind-induced errors. The Brue catchment (135 km2) in Southwest England covering 28 radar pixels and 49 rain gauges is an experimental catchment, where the radar central beam height varies between 500 and 700 m. The 20 typical events (with durations of 6-36 h) are chosen to assess the correlation between hourly radar and gauge rainfall surfaces. It is found that for most events, the improved rates of correlation coefficients are greater than 10%, and nearly half of the events increase by 20%. With the proposed method, except four events, all the event-averaged correlation values are greater than 0.5. This work is the first study to tackle both wind effects on radar and rain gauges, which could be considered as one of the essential components in processing radar observational data in its hydrometeorological applications.
such as the monopulse radar, Doppler Beam Sharpening (DBS), developed by Wiley in the early 1950s [Ulaby et al., 1982], are used to improve the result. However, the various optimization techniques do not work well for radarAngular and range interferometry to refine weather radar resolution Guifu Zhang School
Kruger, A.; Krajewski, W. F.; Goska, R.; Domaszczynski, P.; Gunyon, C.; Smith, J. A.; Baeck, M. L.
Hydro-NEXRAD is a software system with web-based user interface for obtaining historical customized NEXRAD-based radar-rainfall maps (products) from some 40 WSR-88D radars covering mainly the central and eastern U.S. These products have increased spatial and temporal resolution in comparison to the operational products available from the US National Weather Service. Rainfall researchers and hydrologists can request customized products by selecting various algorithmic modules and parameter values. The produced rainfall maps can be projected on a grid of choice. The output is formatted for ingest by geographic information systems and mapping software. The authors present the system architecture, the database extent and the possibilities of including additional algorithms in the future versions. They illustrate the utility of the software with several applications where side-by-side comparisons of various products allow studies of uncertainty propagation and sensitivity analysis. One of the comparisons presented involves the NWS products obtained with the Precipitation Processing System. Since one of the features of Hydro-NEXRAD is repeatability of the results, the system promotes systematic studies of new algorithms, comparisons with rain gauge data and error modeling, and uncertainty propagation in hydrologic applications. The system can be considered as prototype of large-scale data dissemination system broadly customized for a specific application. The system could be evolved into a world-wide database of radar data serving the needs of global remote sensing research community.
Robinson, Michael; Steiner, Matthias; Wolff, David B.; Ferrier, Brad S.; Kessinger, Cathy; Einaudi, Franco (Technical Monitor)
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.
Chandra, Chandrasekar V.; Chen*, Haonan
Urban flash flood is one of the most commonly encountered hazardous weather phenomena. Unfortunately, the rapid urbanization has made the densely populated areas even more vulnerable to flood risks. Hence, accurate and timely monitoring of rainfall at high spatiotemporal resolution is critical to severe weather warning and civil defense, especially in urban areas. However, it is still challenging to produce high-resolution products based on the large S-band National Weather Service (NWS) Next-Generation Weather Radar (NEXRAD), due to the sampling limitations and Earth curvature effect. Since 2012, the U.S. National Science Foundation Engineering Research Center (NSF-ERC) for Collaborative Adaptive Sensing of the Atmosphere (CASA) has initiated the development of Dallas-Fort Worth (DFW) radar remote sensing network for urban weather hazards mitigation. The DFW urban radar network consists of a combination of high-resolution X-band radars and a standard NWS NEXRAD radar operating at S-band frequency. High-resolution quantitative precipitation estimation (QPE) is one of the major research goals in the deployment of this urban radar network. It has been shown in the literature that the dual-polarization radar techniques can improve the QPE accuracy over traditional single-polarization radars by rendering more measurements to enhance the data quality, providing more information about rain drop size distribution (DSD), and implying more characteristics of different hydrometeor types. This paper will present the real-time dual-polarization CASA DFW QPE system, which is developed via fusion of observations from both the high-resolution X band radar network and the S-band NWS radar. The specific dual-polarization rainfall algorithms at different frequencies (i.e., S- and X-band) will be described in details. In addition, the fusion methodology combining observations at different temporal resolution will be presented. In order to demonstrate the capability of rainfall estimation of the CASA DFW QPE system, rainfall measurements from ground rain gauges will be used for evaluation purposes. This high-resolution QPE system is used for urban flash flood forecasting when coupled with hydrological models.
Collis, S. M.; Giangrande, S. E.; Helmus, J.; Troemel, S.
Radars that transmit and receive signals in polarizations aligned both horizontal and vertical to the horizon collect a number of measurements. The relation both between these measurements and between measurements and desired microphysical quantities (such as rainfall rate) is complicated due to a number of scattering mechanisms. The result is that there ends up being an intractable number of often incompatible techniques for extracting geophysical insight. This presentation will discuss methods developed by the Atmospheric Measurement Climate (ARM) Research Facility to streamline the creation of application chains for retrieving rainfall properties for the purposes of fine scale model evaluation. By using a Common Data Model (CDM) approach and working in the popular open source Python scientific environment analysis techniques such as Linear Programming (LP) can be bought to bear on the task of retrieving insight from radar signals. This presentation will outline how we have used these techniques to detangle polarimetric phase signals, estimate a three-dimensional precipitation field and then objectively compare to cloud resolving model derived rainfall fields from the NASA/DoE Mid-Latitude Continental Convective Clouds Experiment (MC3E). All techniques show will be available, open source, in the Python-ARM Radar Toolkit (Py-ART).
Marra, Francesco; Lokshin, Anton; Notarpietro, Riccardo; Gabella, Marco; Branca, Marco; Bonfil, David; Morin, Efrat
Weather radars provide rainfall estimates with high spatial and temporal resolutions over wide areas. X-Band weather radars are of relatively low-cost and easy to be handled and maintained, moreover they offer extremely high spatial and temporal resolutions and are therefore object of particular interest. Main drawback of these instruments lies on the quantitative accuracy, that can be significantly affected by atmospheric attenuation. Distributed rainfall information is a key issue when hydrological applications are needed for small space-time scale phenomena such as flash floods and debris flows. Moreover, such detailed measurements represent a great benefit for agricultural management of areas characterized by substantial rainfall variability. Two single polarization, single elevation, non-Doppler X-Band weather radars are operational since Oct-2012 in the northern Negev (Israel). Mean annual precipitation over the area drops dramatically from 500 mm/yr at the Mediterranean coast to less than 50 mm/yr at the hyper-arid region near the Dead Sea in less than a 100 km distance. The dryer region close to the Dead Sea is prone to flash floods that often cause casualties and severe damage while the western Mediterranean region is extensively used for agricultural purposes. Measures from a C-Band weather radar located 40-120 km away and from a sparse raingauge network (density ~1gauge/450km2) are also available. C-Band rainfall estimates are corrected using combined physically-based and empirical adjustment of data. The aim of this study is to assess the quantitative accuracy of X-Band rainfall estimates with respect to the combined use of in situ measurements and C-Band observations. Results from a set of storms occurred during the first years of measurements are discussed paying particular attention to: (i) wet radome attenuation, (ii) range dependent degradation including attenuation along the path and (iii) systematic effects related to the Mediterranean to hyper-arid climatic transition.
- eterization and drop size distribution, (ii) methods used to smooth profiles of differential propagation phase sensitive to drop size distribution and axisratio parameterization, differences between Zh- and Kdp-based rainfall estimates to beam shielding for C-band radar data during four typical rain events encountered
We are now research several sever hazards of meteorological phenomena, for example, thunderstorm, hail, heavy rain-fall, tornado, etc., by using Phased Array Weather Radar (PAWR). In this paper, we present our analyses between PAWRs echo data temporal variations and thunderstorms lightning activity, hail fall and/or heavy rain-fall rate, etc. We will develop nowcast and/or forecast methods of sever hazards and, in near future, we will prepare new prediction numerical model of sever hazards by using CReSS (Cloud Resolving Storm Simulator).
Wolfe, Eric E.; Flikkema, Paul G.; Henning, Rudolf E.
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.
Hadley, Jennifer Lyn
in their model. This data is now being used in a near real-time flood warning system application. Ogden et al. (2000) used NEXRAD rainfall data with the CASC2D model to evaluate hydrologic prediction of extreme events in urban environments in the Spring... Creek watershed in Fort Collins, Colorado. They found that radar rainfall was useful in hydrologic modeling when gauge adjusted. Otherwise the radar underestimated the rainfall totals in extreme events. Using the uncalibrated rainfall data...
Rasshofer, R. H.; Spies, M.; Spies, H.
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.
Dawen Yang; Toshio Koike; Hiroshi Tanizawa
Through utilizing weather radar measurements, the present research explores the possibility of applying a coupled distributed hydrological model with reservoir operations to flood forecasting and control in the Okutone basin, located in the upstream region of the Tone River. The Tone River basin often suffers from heavy rainfall events as a result of rainy season frontal activity, typhoons and cumulus
Rosenfeld, Daniel; Wolff, David B.; Amitai, Eyal
A simplified probability matching method is introduced that relies on matching the unconditional probabilities of R and Ze, using data from a C-band radar and raingage network near Darwin, Australia. This is achieved by matching raingage intensifies to radar reflectivities taken only from small `windows' centered about the gauges in time and space. The windows must be small enough for the gauge to represent the rainfall depth within the radar window yet large enough to encompass the tinting and geometrical errors inherent to such coincident observations. The calculation of the Ze R relation with the window probability marching method (WPMM) is quite straightforward, whereby the unconditional cumulative probabilities of Ze, and R, which are obtained from all of the windows, are matched. In practice Ze and R, having the same cumulative percentile, are related to each other.A relatively small sample size (about 600 mm for all gauges combined) is required to achieve a stable Ze R relation with a standard deviation of 15% of R for a given Ze. The obtained Ze R relations are curved lines in log-log space and therefore may better represent the transformation of Ze into R than any straight-line power law.The WPMM also performs significantly better for rainfall integrations than power law. The standard deviation of the WPMM rainfall integration, after correction for systematic bias errors, is only two-thirds that of the standard deviation obtained when using a power law based on disdrometer measured drop size distribution.Additional improvement in the accuracy of the WPMM is provided upon its application to data that has been objectively clarified into different rain regimes, which is the topic of another related study in this journal.
Maidment, D. R.; Robayo, O.
The Arc Hydro geographic data model for representing water resources features of the landscape is a customization of ArcGIS for representation of water resources features of the landscape. Arc Hydro is used here to integrate the HEC-HMS and HEC-RAS flood simulation models so as to transform Nexrad radar rainfall data into flood inundation maps through the HEC models. An automated workflow sequence is established using Map2Map: an ArcGIS version 9 toolbox and Model Builder that accomplishes all the desired data transformations between the GIS and the two hydrologic models including time series data exchange for rainfall, flows and water surface elevations. An example application is presented for Salado and Rosillo Creeks in San Antonio.
, Amherst MA Abstract-- Tornado, hazardous weather and flood detection radars demand high-throughput, high-based system has been successfully integrated with a radar optimized for tornado detection and deployed, and perform various processing tasks to cast the raw data into an intelligible and meaningful format
-hydrometeors. In this work, a multi-sensor physically based algorithm is designed to classify weather/non-weather radar Radar-1988 Doppler (WSR-88D) radars and 30+ Canadian weather radars to generate a threeA multi-sensor physically based weather/non-weather radar echo classifier using polarimetric
Petersen, Walter A.; Gatlin, Patrick N.; Felix, Mariana; Carey, Lawrence D.
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.
Dai, Qiang; Han, Dawei; Zhuo, Lu; Huang, Jing; Islam, Tanvir; Srivastava, Prashant K.
A large number of radar rainfall uncertainty (RRU) models have been proposed due to many error sources in weather radar measurements. It is recognized that these models should be integrated into overall uncertainty analysis schemes with other kinds of model uncertainties such as model parameter uncertainty when the radar rainfall is applied in hydrological modeling. We expect that the RRU model can be expressed in a mathematically extensible and simple format. However, the complexity of the RRU has been growing as more and more factors are considered such as spatio-temporal dependence and non-Gaussian distribution. This study analyzes how the RRU propagates through a hydrological model (the Xinanjiang model) and investigates which features of the RRU model have significant impacts on flow simulation. A RRU model named Multivariate Distributed Ensemble Generator (MDEG) is implemented in the Brue catchment in England under different model complexities. The generated ensemble rainfall values by MDEG are then input into the Xinanjiang model to produce uncertainty bands of ensemble flows. Comparison of five important indicators that describe the characteristics of uncertainty bands shows that the ensemble flows generated by MDEG with non-Gaussian marginal and joint distributions are close to the ones with Gaussian distributions. In addition, the dispersion of the uncertainty bands increases dramatically with the growth of the MDEG model complexity. It is concluded that the Gaussian marginal distribution and spatio-temporal dependence using Gaussian copula is considered to be the preferred configuration of the MDEG model for hydrological model uncertainty analysis. Further studies should be carried out in a variety of catchments under different climate conditions and geographical locations to check if the conclusion is valid beyond the Brue catchment under the British climate.
7.8 CHARACTERISTICS OF MICROBURST EVENTS OBSERVED WITH THE NATIONAL WEATHER RADAR TESTBED PHASED events. Microbursts are small-scale ( in thunderstorms that frequently cause damage to property and are a hazard to aviators. Many severe microbursts
Buler, Jeffrey J.; Randall, Lori A.; Fleskes, Joseph P.; Barrow, Wylie C.; Bogart, Tianna; Kluver, Daria
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.
Dunbar, Brian; Mittelman, Jeff
The National Weather Service (NWS), Federal Aviation Administration (FAA), and Department of Defense are in the process of fielding the Next Generation Weather Radars (NEXRAD). These doppler weather radars, also known as Weather Surveillance Radar (WSR)-88D, will be replacing the WSR-57 and WSR-74 weather radars in use today. The NEXRAD data will be used by the FAA's Advanced Automation System (AAS) in place of the Air Route Surveillance Radar (ARSR) weather data currently being used by air traffic controllers. Because the NEXRAD's scanning strategy is more time consuming than the ARSR's, there have been some concerns expressed within the FAA about using 'untimely' NEXRAD data in an Air Traffic Control (ATC) environment. In response to these concerns, the FAA's Center for Advanced Aviation System Development (CAASD) at MITRE conducted a study, under the sponsorship of the FAA's National Airspace System (NAS) System Engineering Service (ASE), to assess the relative ability of NEXRAD's and ARSR's to detect and present significant weather in order to determine the operational impact of using NEXRAD data in lieu of ARSR data. The NEXRAD/ARSR operational comparison study is documented.
Benedetti, A.; Lopez, P.; Moreau, E.; Bauer, P.; Venugopal, V.
A validation of passive microwave adjusted rainfall analyses of tropical cyclones using spaceborne radar data is presented. This effort is part of the one-dimensional plus four-dimensional variational (1D+4D-Var) rain assimilation project that is being carried out at the European Centre for Medium-Range Weather Forecasts (ECMWF). Brightness temperatures or surface rain rates from the Tropical Rainfall Measuring Mission (TRMM) satellite are processed through a 1D-Var retrieval to derive values of total column water vapor that can be ingested into the operational ECMWF 4D-Var. As an indirect validation, the precipitation fields produced at the end of the 1D-Var minimization process are converted into equivalent radar reflectivity at the frequency of the TRMM precipitation radar (13.8 GHz) and are compared with the observations averaged at model resolution. The averaging process is validated using a sophisticated downscaling/upscaling approach that is based on wavelet decomposition. The precipitation radar measurements are ideal for this validation exercise, being approximately collocated with but completely independent of the TRMM Microwave Imager (TMI) radiometer measurements. Qualitative and statistical comparisons between radar observations and retrievals from the TMI-derived surface rain rates and from TMI radiances are made using 17 well-documented tropical cyclone occurrences between January and April of 2003. Several statistical measures, such as bias, root-mean-square error, and Heidke skill score, are introduced to assess the 1D-Var skill as well as the model background skill in producing a realistic rain distribution. Results show a good degree of skill in the retrievals, especially near the surface and for medium heavy rain. The model background produces precipitation in the domain that is sometimes in excess with respect to the observations, and it often shows an error in the location of precipitation maxima. Differences between the two 1D-Var approaches are not large enough to make final conclusions regarding the advantages of one method over the other. Both methods are capable of redistributing the rain patterns according to the observations. It appears, however, that the brightness temperature approach is in general more effective in increasing precipitation amounts at moderate-to-high rainfall rates.
Marra, F.; Nikolopoulos, E.; Borga, M.; Creutin, J. D.
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 estimations are obtained taking into account both vertical (VPR) and radial (attenuation, screening) sources of error, and are adjusted with raingauges to provide reference rainfall estimates at the ground. Radar- and raingauge- based precipitation thresholds are identified and are compared, showing that a bias arises when using raingauge measurements for threshold assessment. The bias is related to the spatial variability characteristics of the considered storms and to the relative geometry of raingauges and debris flows. Even though the weather radar estimation uncertainty also impact the precipitation threshold identification methodology, no bias is reported for this last case. This provides a basis to identify opportunities in the use of radar-based estimates for debris flow warning in alpine regions. Key challenges are also identified, including the requirement for high quality, high resolution radar-based precipitation reanalyses and problems in areas with mixed or poor radar-coverage.
Asfaw, Alemayehu; Shucksmith, James; Smith, Andrea; MacDonald, Ken
The impacts of climate change and growing water use are likely to put considerable pressure on water resources and the environment. In the UK, a reform to surface water abstraction policy has recently been proposed which aims to increase the efficiency of using available water resources whilst minimising impacts on the aquatic environment. Key aspects to this reform include the consideration of dynamic rather than static abstraction licensing as well as introducing water trading concepts. Dynamic licensing will permit varying levels of abstraction dependent on environmental conditions (i.e. river flow and quality). The practical implementation of an effective dynamic abstraction strategy requires suitable flow forecasting techniques to inform abstraction asset management. Potentially the predicted availability of water resources within a catchment can be coupled to predicted demand and current storage to inform a cost effective water resource management strategy which minimises environmental impacts. The aim of this work is to use a historical analysis of UK case study catchment to compare potential water resource availability using modelled dynamic abstraction scenario informed by a flow forecasting model, against observed abstraction under a conventional abstraction regime. The work also demonstrates the impacts of modelling uncertainties on the accuracy of predicted water availability over range of forecast lead times. The study utilised a conceptual rainfall-runoff model PDM - Probability-Distributed Model developed by Centre for Ecology & Hydrology - set up in the Dove River catchment (UK) using 1km2 resolution radar rainfall as inputs and 15 min resolution gauged flow data for calibration and validation. Data assimilation procedures are implemented to improve flow predictions using observed flow data. Uncertainties in the radar rainfall data used in the model are quantified using artificial statistical error model described by Gaussian distribution and propagated through the model to assess its influence on the forecasted flow uncertainty. Furthermore, the effects of uncertainties at different forecast lead times on potential abstraction strategies are assessed. The results show that over a 10 year period, an average of approximately 70 ML/d of potential water is missed in the study catchment under a convention abstraction regime. This indicates a considerable potential for the use of flow forecasting models to effectively implement advanced abstraction management and more efficiently utilize available water resources in the study catchment.
Wright, D. B.; Smith, J. A.; Baeck, M. L.; Villarini, G.
A 10-year radar rainfall dataset is being developed for the Atlanta, Georgia metropolitan area using the Hydro-NEXRAD algorithms. Radar rainfall fields are constructed at 15 minute time resolution and 1 km spatial resolution; observations from a dense network of rain gages are used for multiplicative bias correction. The high-resolution dataset will permit the investigation of urban effects on the initiation and evolution of heavy rainfall events. In addition, the climatology of extreme rainfall-runoff relationships will be examined with the aim of improving the understanding of the water balance and flood response of urban catchments during extreme rainfall events. Analyses relating the temporal and spatial distribution of rainfall to basin scale and land-use/land-cover characteristics will assist in developing urban flood frequency relationships. Events of particular interest are the floods of September 20-21, 2009 and May 3-4, 2010, which caused heavy damage and fatalities in portions of the southeastern US including Atlanta. Similar bias-corrected radar datasets in development for the Baltimore, Charlotte, and Milwaukee metropolitan areas will allow for the comparison of climatology of extreme rainfall and urban flooding in different regions of the United States and under different climate regimes.
Teschl, Reinhard; Randeu, Walter; Teschl, Franz
Weather radar networks provide data with good spatial coverage and temporal resolution. Hence they are able to describe the variability of precipitation. Typical radar stations determine the rain rate for every square kilometre and make a full volume scan within about 5 minutes. A weakness however, is their often poor metering precision limiting the applicability of the radar for hydrological purposes. In contrast to rain gauges, which measure precipitation directly on the ground, the radar determines the reflectivity aloft and remote. Due to this principle, several sources of possible errors occur. Therefore improving the radar estimates of rainfall is still a vital topic in radar meteorology and hydrology. This paper presents data-driven approaches to improve radar estimates of rainfall by mapping radar reflectivity measurements Z to rain gauge data R. The analysis encompasses several input configurations and data-driven models. Reflectivity measurements at a constant altitude and the vertical profiles of reflectivity above a rain gauge are used as input parameters. The applied models are Artificial Neural Network (ANN), Model Tree (MT), and IBk a k-nearest-neighbour classifier. The relationship found between the data of a rain gauge and the reflectivity measurements is subsequently applied to another site with comparable terrain. Based on this independent dataset the performance of the data-driven models in the various input configurations is evaluated. For this study, rain gauge and radar data from the province of Styria, Austria, were available. The data sets extend over a two-year period (2001 and 2002). The available rain gauges use the tipping bucket principle with a resolution of 0.1 mm. Reflectivity measurements are obtained from the Doppler weather radar station on Mt. Zirbitzkogel (by courtesy of AustroControl GmbH). The designated radar is a high-resolution C-band weather-radar situated at an altitude of 2372 m above mean sea level. The data-driven models exhibit different performances on the various input configurations. Also data transformations were applied. The logarithm recommends itself for this transformation because the original Z-R-relationship is a power function, and the logarithm linearises this non-linear relationship. The MT which is a piecewise linear model performs best on logarithmised data. The IBk works well when transforming the reflectivity data in rain rate first. Overall the ANN exhibits the best performance showing a 10 % improvement in correlation and RMSE compared to the standard Z-R-relationship. When applying the vertical profile of reflectivity as input parameter, the correlation exhibits a more than 30 % improvement. The results indicate that the vertical profile of reflectivity provided by weather radars yields not only information on the type of precipitation, whether it is stratiform or convective. In data-driven models the vertical profile of reflectivity can help to get better estimates of rain rates on the ground, even in mountainous terrain without low-altitude radar measurements.
Ahm, Malte; Thorndahl, Søren; Rasmussen, Michael R; Bassø, Lene
This paper presents a method for estimating runoff coefficients of urban drainage subcatchments based on a combination of high resolution weather radar data and flow measurements from a downstream runoff sensor. By utilising the spatial variability of the precipitation it is possible to estimate the runoff coefficients of the separate subcatchments. The method is demonstrated through a case study of an urban drainage catchment (678 ha) located in the city of Aarhus, Denmark. The study has proven that it is possible to use corresponding measurements of the relative rainfall distribution over the catchment and downstream runoff measurements to identify the runoff coefficients at subcatchment level. PMID:24056426
Chiswell, S.; Buckley, R.
During the year 2008, the United States National Weather Service (NWS) completed an eight fold increase in sampling capability for weather radars to 250 m resolution. This increase is expected to improve warning lead times by detecting small scale features sooner with increased reliability; however, current NWS operational model domains utilize grid spacing an order of magnitude larger than the radar data resolution, and therefore the added resolution of radar data is not fully exploited. The assimilation of radar reflectivity and velocity data into high resolution numerical weather model forecasts where grid spacing is comparable to the radar data resolution was investigated under a Laboratory Directed Research and Development (LDRD) 'quick hit' grant to determine the impact of improved data resolution on model predictions with specific initial proof of concept application to daily Savannah River Site operations and emergency response. Development of software to process NWS radar reflectivity and radial velocity data was undertaken for assimilation of observations into numerical models. Data values within the radar data volume undergo automated quality control (QC) analysis routines developed in support of this project to eliminate empty/missing data points, decrease anomalous propagation values, and determine error thresholds by utilizing the calculated variances among data values. The Weather Research and Forecasting model (WRF) three dimensional variational data assimilation package (WRF-3DVAR) was used to incorporate the QC'ed radar data into input and boundary conditions. The lack of observational data in the vicinity of SRS available to NWS operational models signifies an important data void where radar observations can provide significant input. These observations greatly enhance the knowledge of storm structures and the environmental conditions which influence their development. As the increase in computational power and availability has made higher resolution real-time model simulations possible, the need to obtain observations to both initialize numerical models and verify their output has become increasingly important. The assimilation of high resolution radar observations therefore provides a vital component in the development and utility of numerical model forecasts for both weather forecasting and contaminant transport, including future opportunities to improve wet deposition computations explicitly.
Anderson, D. J.; Bull, J. S.; Chisholm, J. P.
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.
Approximate Bayesian Inference for Reconstructing Velocities of Migrating Birds from Weather Radar network of weather radars in the US hold detailed information about the continent-scale migratory of a radar station. This is part of a larger project to quantify bird migration at large scales using weather
Doppler weather radar based nowcasting of cyclone Ogni Soma Sen Roy1, , V Lakshmanan2 , S K Roy@yahoo.com In this paper, we describe offline analysis of Indian Doppler Weather Radar (DWR) data from cyclone Ogni using). Processing of Indian Doppler Weather Radar (DWR) data for nowcasting application under the sub-project Local
Stephen C. Gerwin
The Washington Suburban Sanitary Commission (WSSC) has tied into the National Weather Service radar system to take measures against the disruptions in water service caused by power outages during frequent severe summer thunderstorms. Advance warnings of potential outages enable the utility to fill elevated storage tanks to maximal capacities, and pumping can be done during offpeak periods when electric rates
Kucera, Paul; Klepp, Christian
During the period of 9-16 September 2013, a large area of greater than 150 mm of rain, with local amounts of up to 450 mm, fell over a large part of the Colorado Front Range foothills and adjacent plains. This extreme rainfall event caused severe flooding of main river channels and some localized flash flooding which resulted in millions of dollars of damage to private and public properties. The rainfall regime associated with this extreme precipitation event was atypical of storms usually observed in this region. As a result, the radar rainfall algorithms tuned for this region significantly underestimated the total amount of rainfall. In order to quantify the underestimation and provide insight for improving the radar rainfall estimates for this unique precipitation regime, a comparison study has been conducted using data from several disdrometers that were operating throughout the event. Disdrometers observed over 5000 minutes of rainfall during the event. Analysis of the raindrop spectra indicated that most of the rainfall was comprised of a large number of small drops (< 2 mm in diameter). The raindrop spectra have been stratified by the precipitation regime. For these different regimes, new radar rainfall estimators are being derived from the raindrop spectra. The new estimators will be applied to the radar data to provide new rainfall estimates. These estimates will be evaluated using independent rain gauge data. The presentation will provide an overview of the Colorado Flood and a summary of results from the precipitation analysis.
Brad Isom; Robert Palmer; Redmond Kelley; John Meier; David Bodine; Mark Yeary; Boon Leng Cheong; Yan Zhang; Tian-You Yu; Mike Biggerstaff
Rapid updates are a highly desired feature in the field of mobile weather radars. Various techniques have been used to improve volume update times, including the use of agile and multi-beam radars. Imaging radars, similar in some respects to phased arrays, steer the radar beam in software, thus requiring no physical motion. In contrast to phased arrays, imaging radars gather
of weather radar data. SRDC was tested on Level II reflectivity product data from several S-band Doppler. Index Terms--radar signal processing, compression, high- resolution data, Doppler radar I. INTRODUCTION EATHER Surveillance Radar 1988-Doppler (WSR- 88D) radars have several operating modes and scanning
Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Delrieu, G.; Uijlenhoet, R.
This paper presents a novel approach to estimate the vertical profile of reflectivity (VPR) from volumetric weather radar data using both a traditional Eulerian as well as a newly proposed Lagrangian implementation. For this latter implementation, the recently developed Rotational Carpenter Square Cluster Algorithm (RoCaSCA) is used to delineate precipitation regions at different reflectivity levels. A piecewise linear VPR is estimated for either stratiform or neither stratiform/convective precipitation. As a second aspect of this paper, a novel approach is presented which is able to account for the impact of VPR uncertainty on the estimated radar rainfall variability. Results show that implementation of the VPR identification and correction procedure has a positive impact on quantitative precipitation estimates from radar. Unfortunately, visibility problems severely limit the impact of the Lagrangian implementation beyond distances of 100 km. However, by combining this procedure with the global Eulerian VPR estimation procedure for a given rainfall type (stratiform and neither stratiform/convective), the quality of the quantitative precipitation estimates increases up to a distance of 150 km. Analyses of the impact of VPR uncertainty shows that this aspect accounts for a large fraction of the differences between weather radar rainfall estimates and rain gauge measurements.
Pazmany, Andrew L.
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.
Bech, Joan; Pineda, Nicolau; Rigo, Tomeu; Aran, Montserrat; Amaro, Jéssica; Gayà, Miquel; Arús, Joan; Montanyà, Joan; der Velde, Oscar van
This study presents an analysis of a severe weather case that took place during the early morning of the 2nd of November 2008, when intense convective activity associated with a rapidly evolving low pressure system affected the southern coast of Catalonia (NE Spain). The synoptic framework was dominated by an upper level trough and an associated cold front extending from Gibraltar along the Mediterranean coast of the Iberian Peninsula to SE France, which moved north-eastward. South easterly winds in the north of the Balearic Islands and the coast of Catalonia favoured high values of 0-3 km storm relative helicity which combined with moderate MLCAPE values and high shear favoured the conditions for organized convection. A number of multicell storms and others exhibiting supercell features, as indicated by Doppler radar observations, clustered later in a mesoscale convective system, and moved north-eastwards across Catalonia. They produced ground-level strong damaging wind gusts, an F2 tornado, hail and heavy rainfall. Total lightning activity (intra-cloud and cloud to ground flashes) was also relevant, exhibiting several classical features such as a sudden increased rate before ground level severe damage, as discussed in a companion study. Remarkable surface observations of this event include 24 h precipitation accumulations exceeding 100 mm in four different observatories and 30 minute rainfall amounts up to 40 mm which caused local flash floods. As the convective system evolved northward later that day it also affected SE France causing large hail, ground level damaging wind gusts and heavy rainfall.
Bech, Joan; Berenguer, Marc
Heavy precipitation events and subsequent flash floods are one of the most dramatic hazards in many regions such as the Mediterranean basin as recently stressed in the HyMeX (HYdrological cycle in the Mediterranean EXperiment) international programme. The focus of this study is to assess the quality of very short range (below 3 hour lead times) precipitation forecasts based on weather radar nowcasting system. Specific nowcasting amounts of 10 and 30 minutes generated with a nowcasting technique (Berenguer et al 2005, 2011) are compared against raingauge observations and also weather radar precipitation estimates observed over Catalonia (NE Spain) using data from the Meteorological Service of Catalonia and the Water Catalan Agency. Results allow to discuss the feasibility of issuing warnings for different precipitation amounts and lead times for a number of case studies, including very intense convective events with 30minute precipitation amounts exceeding 40 mm (Bech et al 2005, 2011). As indicated by a number of verification scores single based radar precipitation nowcasts decrease their skill quickly with increasing lead times and rainfall thresholds. This work has been done in the framework of the Hymex research programme and has been partly funded by the ProFEWS project (CGL2010-15892). References Bech J, N Pineda, T Rigo, M Aran, J Amaro, M Gayà, J Arús, J Montanyà, O van der Velde, 2011: A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis. Atmospheric Research 100:621-637 http://dx.doi.org/10.1016/j.atmosres.2010.12.024 Bech J, R Pascual, T Rigo, N Pineda, JM López, J Arús, and M Gayà, 2007: An observational study of the 7 September 2005 Barcelona tornado outbreak. Natural Hazards and Earth System Science 7:129-139 http://dx.doi.org/10.5194/nhess-7-129-2007 Berenguer M, C Corral, R Sa0nchez-Diezma, D Sempere-Torres, 2005: Hydrological validation of a radar based nowcasting technique. Journal of Hydrometeorology 6: 532-549 http://dx.doi.org/10.1175/JHM433.1 Berenguer M, D Sempere, G Pegram, 2011: SBMcast - An ensemble nowcasting technique to assess the uncertainty in rainfall forecasts by Lagrangian extrapolation. Journal of Hydrology 404: 226-240 http://dx.doi.org/10.1016/j.jhydrol.2011.04.033
Licznar, Pawe?; Deidda, Roberto
Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal analysis is carried out assuming Taylor's hypothesis to hold and the advection velocity needed to rescale the time dimension is assumed to be equal about 16 km/h. This assumption is verified by the analysis of autocorrelation functions along the x and y directions of "rainfall cubes" and along the time axis rescaled with assumed advection velocity. In general for analyzed rainfall sequences scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. However in most cases scaling break is identified for spatial scales between 4 and 8, corresponding to spatial dimensions of 16 km to 32 km. It is assumed that the scaling break occurrence at these particular scales in central Poland conditions could be at least partly explained by the rainfall mesoscale gap (on the edge of meso-gamma, storm-scale and meso-beta scale).
and the Precipitating Clouds product, supervised classification of the radar echoes into clutter and precipitationERADERAD 20062006Proceedings ofProceedings of Detecting weather radar clutter using satellite results from investigations into detection of weather radar clutter by data fusion with satellite
in the European Weather Radar Network. The third phase of Fig. 1. Overview and interaction of program elements Radar Network. II. LAYOUT OF THE PROGRAM Since 1 January 2007 Iwan Holleman (KNMI) is program managerUpdate on the European Weather Radar Network (OPERA) Iwan Holleman, Laurent Delobbe, and Anton
Abstract--Enabled by a dense network of Doppler weather radars with overlapping coverage-power, low-cost, short-range, Doppler weather radars whose short-range allows them to see down low each radar periodically sampling its surroundings with sit-and-spin volume coverage patterns
Lee, J.-K.; Kim, J.-H.; Suk, M.-K.
There are many potential sources of bias in the radar rainfall estimation process. This study classified the biases from the rainfall estimation process into the reflectivity measurement bias and QPE model bias and also conducted the bias correction methods to improve the accuracy of the Radar-AWS Rainrate (RAR) calculation system operated by the Korea Meteorological Administration (KMA). For the Z bias correction, this study utilized the bias correction algorithm for the reflectivity. The concept of this algorithm is that the reflectivity of target single-pol radars is corrected based on the reference dual-pol radar corrected in the hardware and software bias. This study, and then, dealt with two post-process methods, the Mean Field Bias Correction (MFBC) method and the Local Gauge Correction method (LGC), to correct rainfall-bias. The Z bias and rainfall-bias correction methods were applied to the RAR system. The accuracy of the RAR system improved after correcting Z bias. For rainfall types, although the accuracy of Changma front and local torrential cases was slightly improved without the Z bias correction, especially, the accuracy of typhoon cases got worse than existing results. As a result of the rainfall-bias correction, the accuracy of the RAR system performed Z bias_LGC was especially superior to the MFBC method because the different rainfall biases were applied to each grid rainfall amount in the LGC method. For rainfall types, Results of the Z bias_LGC showed that rainfall estimates for all types was more accurate than only the Z bias and, especially, outcomes in typhoon cases was vastly superior to the others.
1 Quality Control of Weather Radar Data Using Texture Features and a Neural Network V Lakshmanan1 , Kurt Hondl2 , Gregory Stumpf1 , Travis Smith1 Abstract-- Weather radar data is subject to many to anamalous propagation (AP) or ground clut- ter. Although weather forecasters can usually iden- tify
Merceret, Francis J.; Ward, Jennifer G.
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.
Rainfall Generator for the Rhine Basin Multi-site generation of weather variables for the entire generator for the Rhine Basin 38 3 #12;Summary This is the final report of a project on the development of a rainfall generator for the Rhine basin. The request for this generator arose from the need to study
Kelly, Wallace E. (Inventor); Rand, Timothy W. (Inventor); Uckun, Serdar (Inventor); Ruokangas, Corinne C. (Inventor)
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.
Kozu, Toshiaki; Nakamura, Kenji; Meneghini, Robert; Boncyk, Wayne C.
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.
Holbrook, Vincent Patrick
that are important for the determination of rain deposition. Also, it is obvious that an improperly calibrated radar system as well as the use of an inappropriate 2-R relationship are sources of error. For sampling intervals greater than five minutes the error...SPECIFICATION OF PREDICTORS NECESSARY FOR THE DETERMINATION OF OVER OR UNDERESTIMATION OF RADAR DERIVED TOTAL RAINFALL A Thesis by VINCENT PATRICK HOLBROOK Submitted to the Graduate College of Texas A&M University in partial fulfillment...
Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.
The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.
Atencia, A.; Mediero, L.; Llasat, M. C.; Garrote, L.
The performance of a hydrologic model depends on the rainfall input data, both spatially and temporally. As the spatial distribution of rainfall exerts a great influence on both runoff volumes and peak flows, the use of a distributed hydrologic model can improve the results in the case of convective rainfall in a basin where the storm area is smaller than the basin area. The aim of this study was to perform a sensitivity analysis of the rainfall time resolution on the results of a distributed hydrologic model in a flash-flood prone basin. Within such a catchment, floods are produced by heavy rainfall events with a large convective component. A second objective of the current paper is the proposal of a methodology that improves the radar rainfall estimation at a higher spatial and temporal resolution. Composite radar data from a network of three C-band radars with 6-min temporal and 2 × 2 km2 spatial resolution were used to feed the RIBS distributed hydrological model. A modification of the Window Probability Matching Method (gauge-adjustment method) was applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation by computing new Z/R relationships for both convective and stratiform reflectivities. An advection correction technique based on the cross-correlation between two consecutive images was introduced to obtain several time resolutions from 1 min to 30 min. The RIBS hydrologic model was calibrated using a probabilistic approach based on a multiobjective methodology for each time resolution. A sensitivity analysis of rainfall time resolution was conducted to find the resolution that best represents the hydrological basin behaviour.
WEATHER RADAR IMAGE IN CLIMATOLOGY - After a brief overview about weather radar as a remote sensing instrument, some problems concerning the use of radar images are discussed. The great interest of radar images as a tool in Climatology is pointed out. Finally, a case study about two rainfall events in Nancy (France) in April 1995 is presented.
Smith, James A.; Baeck, Mary Lynn; Villarini, Gabriele; Welty, Claire; Miller, Andrew J.; Krajewski, Witold F.
We introduce a long-term, high-resolution radar rainfall data set for the Baltimore metropolitan area covering the 10-yr period from 2000-2009. Rainfall fields are developed at 15 min time interval and 1 km horizontal resolution for a 17,000-km2 region centered on the Baltimore metropolitan area. The Hydro-NEXRAD system is used as a platform for generating radar rainfall fields. We utilize the high-resolution, 10-yr data set to characterize striking spatial heterogeneities in rainfall for the Baltimore metropolitan region, both in terms of mean rainfall and rainfall extremes. The role of complex terrain (associated with urbanization, the Chesapeake Bay, and mountainous terrain) in controlling spatial heterogeneities of rainfall climatology for the Baltimore study region is discussed. We also characterize the seasonal and diurnal variation of rainfall over the study region using the 10-yr rainfall data set, with particular focus on the diurnal variation of rainfall during the warm season. High-resolution rainfall fields are especially useful for examining the distribution of rainfall from a drainage basin perspective, as illustrated through analyses of basin-averaged rainfall rate for basins of contrasting drainage area and analyses of the duration of dry periods for small urban watersheds. Analyses and methodologies used to develop the long-term Baltimore rainfall data set are broadly applicable to other regions of the United States and in settings around the world with long-term, high-quality radar data sets.
Cunha, Luciana K.; Mandapaka, Pradeep V.; Krajewski, Witold F.; Mantilla, Ricardo; Bradley, Allen A.
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 framework to investigate uncertainty propagation with hydrological models.
Maiello, I.; Ferretti, R.; Gentile, S.; Montopoli, M.; Picciotti, E.; Marzano, F. S.; Faccani, C.
This work is a first assessment of the role of Doppler Weather radar (DWR) data in a mesoscale model for the prediction of a heavy rainfall. The study analyzes the event occurred during 19-22 May 2008 in the urban area of Rome. The impact of the radar reflectivity and radial velocity acquired from Monte Midia Doppler radar, on the assimilation into the Weather Research Forecasting (WRF) model version 3.2, is discussed. The goal is to improve the WRF high resolution initial condition by assimilating DWR data and using ECMWF analyses as First Guess thus improving the forecast of surface rainfall. Several experiments are performed using different set of Initial Conditions (ECMWF analyses and warm start or cycling) and a different assimilation strategy (3 h-data assimilation cycle). In addition, 3DVAR (three-dimensional variational) sensitivity tests to outer loops are performed for each of the previous experiment to include the non-linearity in the observation operators. In order to identify the best ICs, statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a positive impact on the prediction of the heavy rainfall of this event, both assimilating reflectivity and radial velocity, together with conventional observations. Finally, warm start results in more accurate experiments as well as the outer loops strategy.
Very high resolution precipitation climatologies from the Tropical Rainfall Measuring Mission precipitation radar Stephen W. Nesbitt1 and Alison M. Anders2 Received 4 March 2009; revised 6 July 2009 of topography and precipitation, a tropics-wide (±36° latitude) high resolution (0.1°) ten year (1998
Aubert, Yoann; Arnaud, Patrick; Fine, Jean-alain; Cantet, Philippe
The National Research Institute of Science and Technology for Environment and Agriculture (Irstea) has developed an original method for regional rainfall frequency analysis applied on the whole French territory: the SHYREG1 method. It is based on a stochastic hourly rainfall generator. The parameters of the rainfall generator were regionalized at the spatial resolution of 1 km2 thus allowing for the implementation of the model for every 1 km2. Frequency distributions were then derived from long simulated rainfall series for each pixel. Therefore statistical rainfall estimates of various durations (from 1h to 72h) and return periods (from 2 to 1000 years) are made available in a rainfall risk database (intensity-duration-frequency) for the entire French territory. This article presents the application of the SHYREG method in Reunion Island. Reunion Island (with a 2500-km2 surface area) is located in the south-west Indian Ocean. The climate is tropical and characterised by cyclonic rainfall. Tropical cyclones generate heavy rains: during the last one (Bejinsa) in January 2014, rainfall observed exceeded 1000 mm in Cilaos station. Likewise, world records of rainfall, lasting between 5 days (4301 mm in Commerson) and 15 days (6433 mm in Commerson), were observed in Reunion Island during the Hyacinthe Cyclone in January 19802. In mainland France, the calibration of the hourly rainfall generator depends on two seasons (winter from December to May and summer from June to November). However, in order to account for different types of events during a same season, a specific calibration of the hourly rainfall model was necessary. Four types of rainfall event were defined by Météo-France: cyclones, storms, hard rain and rain. Météo-France rainfall data, evenly located over the Island (52 hourly rain gauge stations and 98 daily rain gauge stations), were used to calibrate the hourly rainfall generator. The SHYREG parameters were regionalized based on 17 physiographic maps of the Island (relief, ocean distance, etc.) with a 1-km2 spatial resolution. For return periods of up to 10 years, the SHYREG-estimated rainfall frequency values are consistent with estimates from the GPD law according to the Nash-Sutcliffe criteria. For extreme return periods, we validate SHYREG-based rainfall frequency estimates according to criteria of reliability and stability3 and compare with the GPD performance. The stability of the frequency analysis method is defined by its capacity to produce similar results when calibrated with different data samples, its reliability by its capacity to assign accurate probabilities of occurrence to observations. Results from applying both criteria have shown that the SHYREG method is highly stable and reliable compared to the GPD law.
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
Cifelli, R.; Matrosov, S. Y.; Gochis, D. J.; Kennedy, P.; Moody, J. A.
Polarimetric X-band radar systems have been used increasingly over the last decade for rainfall measurements. Since X-band radar systems are generally less costly, more mobile, and have narrower beam widths (for same antenna sizes) than those operating at lower frequencies (e.g., C and S-bands), they can be used for the "gap-filling" purposes for the areas when high resolution rainfall measurements are needed and existing operational radars systems lack adequate coverage and/or resolution for accurate quantitative precipitation estimation (QPE). The main drawback of X-band systems is attenuation of radar signals, which is significantly stronger compared to frequencies used by "traditional" precipitation radars operating at lower frequencies. The use of different correction schemes based on polarimetric data can, to a certain degree, overcome this drawback when attenuation does not cause total signal extinction. This presentation will focus on examining the use of high-resolution data from the NOAA Earth System Research Laboratory (ESRL) mobile X-band dual polarimetric radar for the purpose of estimating precipitation in a post-wildland fire area. The NOAA radar was deployed in the summer of 2011 to examine the impact of gap-fill radar on QPE and the resulting hydrologic response during heavy rain events in the Colorado Front Range in collaboration with colleagues from the National Center for Atmospheric Research (NCAR), Colorado State University (CSU), and the U.S. Geological Survey (USGS). A network of rain gauges installed by NCAR, the Denver Urban Drainage Flood Control District (UDFCD), and the USGS are used to compare with the radar estimates. Supplemental data from NEXRAD and the CSU-CHILL dual polarimetric radar are also used to compare with the NOAA X-band and rain gauges. It will be shown that rainfall rates and accumulations estimated from specific differential phase measurements (KDP) at X-band are in good agreement with the measurements from the gauge network during heavy rain and rain/hail mixture events. The X-band radar measurements also were generally successful in capturing the high spatial variability in convective rainfall, which caused post-fire debris flows.
Tanelli, Simone; Im, Eastwood; Kobayashi, Satoru; Mascelloni, Roberto; Facheris, Luca
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.
Dokter, Adriaan M; Liechti, Felix; Stark, Herbert; Delobbe, Laurent; Tabary, Pierre; Holleman, Iwan
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
kW vs 1MW #12;Future Work · Doppler Off-The-Grid radar · Improve system performance · Lower currentOff-The-Grid X-band Weather Radar Network for the West Coast of Puerto Rico José A. Ortiz CASA UPRM in the lower atmosphere which cannot be sampled due to the earth curvature and distance between the radar
Nasta, P.; Gates, J. B.; Lock, N.; Houston, A. L.
Groundwater recharge rates through the unsaturated zone emerge from complex interactions within the soil-vegetation-atmosphere system that derive from nonlinear relationships amongst atmospheric boundary conditions, plant water use and soil hydraulic properties. While it is widely recognized that hydrologic models must capture soil water dynamics in order to provide reliable recharge estimates, information on episodic recharge generation remains uncommon, and links between storm-scale weather patterns and their influence on recharge is largely unexplored. In this study, the water balance of a heterogeneous one-dimensional soil domain (3 m deep) beneath a typical rainfed corn agro-ecosystem in eastern Nebraska was numerically simulated in HYDRUS-1D for 12 years (2001-2012) on hourly time steps in order to assess the relationships between weather events and episodic recharge generation. WSR-88D weather radar reflectivity data provided both rainfall forcing data (after estimating rain rates using the z/r ratio method) and a means of storm classification on a scale from convective to stratiform using storm boundary characteristics. Individual storm event importance to cumulative recharge generation was assessed through iterative scenario modeling (773 total simulations). Annual cumulative recharge had a mean value of 9.19 cm/yr (about 12 % of cumulative rainfall) with coefficient of variation of 73%. Simulated recharge generation events occurred only in late winter and spring, with a peak in May (about 35% of total annual recharge). Recharge generation is observed primarily in late spring and early summer because of the combination of high residual soil moisture following a winter replenishment period, heavy convective storms, and low to moderate potential evapotranspiration rates. During the growing season, high rates of root water uptake cause rapid soil water depletion, and the concurrent high potential evapotranspiration and low soil moisture prevented recharge generation until late winter, even when intense convective storms took place. For this reason, about 86% of all precipitation events produce insignificant recharge contributions. Recharge responses to individual storms were nonlinear and did not cluster well with either storm amount or storm classification type. For example, ~7% of rainfall events fall near the 1:1 rainfall/recharge line and these events represent about 37% of cumulative recharge, and individual storms accounted for up to 4% of their annual totals. However, recharge events in late winter are mainly triggered by stratiform precipitation whereas in spring they are generally generated by convective storms. This novel approach to assessing storm-scale recharge may be relevant to several current challenges in the characterization of groundwater recharge processes, including the evaluation of their spatiotemporal distributions and the impacts of climate change on groundwater.
Brady, P.V.; Dorn, R.I.; Brazel, A.J.; Clark, J.; Moore, R.B.; Glidewell, T.
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.
Cho, John Y. N.
Multi-PRI Signal Processing for the Terminal Doppler Weather Radar. Part II: Range developed to combat rangevelocity (RV) ambiguity for the Terminal Doppler Weather Radar (TDWR). In Part I will be a complementary alternative. 1. Introduction The Terminal Doppler Weather Radar (TDWR) ra- dar data acquisition
Ricardo Reinoso-Rondinel; Tian-You Yu; Sebastián Torres
Electronically steered phased array radar was devel- oped in mid-1960s mainly for military applications. It has the capability of instantaneously and dynamically con- trolling beam position on a pulse-to-pulse basis, which allows a single radar to perform multiple functions such as search, target tracking, and weapon controls. The recent-installed phased array radar (PAR) at the Na- tional Weather Radar Testbed
Kitzmiller, D. H.; Guan, S.; Mello, C.; Dai, J.
The Weather Surveillance Radar 1988 (Doppler) (WSR-88D) network contains 142 units within the conterminous United States, 7 units in Alaska, and 4 units in Hawaii. The units are maintained by several agencies of the federal government, including the National Weather Service, the Federal Aviation Administration, and the Department of Defense. Many users of the data require access to observations from multiple radars simultaneously, and various mechanisms have beendevised to create national- and regional-scale geographic composites. Within the National Weather Service, creation of mosaics at local forecast offices can take up a substantial portion of available computing resources. The Meteorological Development Laboratory has undertaken the development of a system that will centrally produce and disseminate a set of mosaic products covering the conterminous United States, thus reducing the need for local production of the products. The effort has been made possible by the recent completion of communications network upgrades that permit rapid central collection of data from all sites within the WSR-88D network. A review of the radar product suite will be presented. The suite presently includes reflectivity, precipitation ccumulation estimates, vertically-integrated liquid water estimates, 18-dBZ echo top heights, and convective storm cell information such as hail indications and Doppler indications of mesocyclones and tornadoes. The operational goal is the production of mosaics at approximately 2-km spatial resolution for reflectivity and 4-km resolution for other fields, on a 5-minute update cycle. Some products are currently made available in graphical format via the World-Wide Web. Substantial progress has been made in developing an automated procedure to identify nonprecipitation echoes, including birds, insects, ground clutter, and anomalous propagation. Tests comparing the outcome of automated target identification with manual identification will be presented.
Banjanin, Zoran B.; Zrnic, Dusan S.
Several methods for canceling ground clutter in Doppler weather radars which operate with staggered pulse repetition times (PRTs) are investigated. A scheme is developed which consists of two filters that operate sequentially, so that the overall filter is time-varying, with periodically changing coefficients. This filter is analyzed theoretically and through simulations for a stagger ratio of 3/2, which extends the unambiguous velocity interval. The amplitude characteristic of the filter over this interval is very good, but the phase characteristic, which is nonlinear in a small part of the interval, requires that a special decision logic be used for velocity estimation. At a signal-to-noise ratio of 10 dB, mean velocity estimates at the output have average errors smaller than 3.5 percent. Thus the scheme could be suitable for operation in environments with ground clutter.
Jin, W.; Qu, Y.
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.
Das, M. K.; Chowdhury, M.; Das, S.
A tornado accompanied with thunderstorm, rainfall and hailstorm affected Brahmanbaria of Bangladesh in the afternoon of 22 March 2013. The tornadic storms are studied based on field survey, ground and radar observations. Low level moisture influx by southerly flow from the Bay of Bengal coupled with upper level westerly jet stream causing intense instability and shear in the wind fields triggered a series of storms for the day. The exact time and locations of the storms are investigated by using the Agartala and Cox's Bazar Doppler Weather Radar (DWR). Subsequently, the storms are simulated by using the WRF-ARW model at 1 km horizontal resolution based on 6 hourly analyses and boundary conditions of NCEP-FNL. Among the typical characteristics of the storms, the CAPE, surface wind speed, flow patterns, T-? gram, rainfall, sea level pressure, vorticity and vertical velocity are studied. Results show that while there are differences of 2-3 hours between the observed and simulated time of the storms, the distances between observed and simulated locations of the storms are several tens of kilometers. The maximum CAPE was generally above 2400 J kg-1 in the case. The maximum intensity of surface wind speed simulated by the model was only 38 m sec-1. This seems to be underestimated. The highest vertical velocity (updraft) simulated by the model was 250 m sec-1 around 800-950 hPa. The updraft reached up to 150 hPa. It seems that the funnel vortex reached the ground, and might have passed some places a few meters above the surface. According to the Fujita Pearson scale, this tornado can be classified as F-2 with estimated wind speed of 50-70 ms-1. Keywords: Tornado, DWR, NCEP-FNL, T-? gram, CAPE.
Randall, Lori A.; Diehl, Robert H.; Wilson, Barry C.; Barrow, Wylie C.; Jeske, Clinton W.
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.
the earlier work by augmenting the profiling radar observations with collocated raindrop disdrometers the operational network of Weather Surveillance Radar-1988 Doppler (WSR-88D) units, which underestimate rain with and without a Radar Bright Band BROOKS E. MARTNER Cooperative Institute for Research in Environmental Sciences
Potter, K. E.
Details of the millimeter wave radar performance are presented which show that with potentially available power sources an all weather capability can be realized. Performance is evaluated as a function of frequency and antenna size, and the use of polarimetry with wide bandwidth/coherent processing is shown to offer potential enhancement for target discrimination. The millimeter wave radar is shown to be potentially capable of satisfying the following functions: take off/landing, terrain following, area correlation, tercom, and acquisition of targets. The above roles can be achieved in an all weather environment making the millimeter wave radar a valuable multifunction airborne radar.
Meneghini, Robert; Atlas, David; Awaka, Jun; Okamoto, Ken'ichi; Ihara, Toshio; Nakamura, Kenji; Kozu, Toshiaki; Manabe, Takeshi
The basic system parameters for the Tropical Rainfall Measuring Mission (TRMM) radar system are frequency, beamwidth, scan angle, resolution, number of independent samples, pulse repetition frequency, data rate, and so on. These parameters were chosen to satisfy NASA's mission requirements. Six candidates for the TRMM rain radar were studied. The study considered three major competitive items: (1) a pulse-compression radar vs. a conventional radar; (2) an active-array radar with a solid state power amplifier vs. a passive-array radar with a traveling-wave-tube amplifier; and (3) antenna types (planar-array antenna vs. cylindrical parabolic antenna). Basic system parameters such as radar sensitivities, power consumption, weight, and size of these six types are described. Trade-off studies of these cases show that the non-pulse-compression active-array radar with a planar array is considered to be the most suitable candidate for the TRMM rain radar at 13.8 GHz.
Mishra, K.; Kruger, A.; Krajewski, W. F.
The recovery of sparsely-sampled signals has long attracted considerable research interest in various fields such as reflection seismology, microscopy, and astronomy. Recently, such recovery techniques have been formalized as a sampling method called compressed sensing (CS) which uses few linear and non-adaptive measurements to reconstruct a signal that is sparse in a known domain. Many radar and remote sensing applications require efficient and rapid data acquisition. CS techniques have, therefore, enormous potential in dramatically changing the way the radar samples and processes data. A number of recent studies have investigated CS for radar applications with emphasis on point target radars, and synthetic aperture radar (SAR) imaging. CS radar holds the promise of compressing-while-sampling, and may yield simpler receiver hardware which uses low-rate ADCs and eliminates pulse compression/matched filter. The need of fewer measurements also implies that a CS radar may need smaller dwell times without significant loss of information. Finally, CS radar data could be used for improving the quality of low-resolution radar observations. In this study, we explore the feasibility of using CS for dual-polarimetric weather radars. In order to recover a signal in CS framework, two conditions must be satisfied: sparsity and incoherence. The sparsity of weather radar measurements can be modeled in several domains such as time, frequency, joint time-frequency domain, or polarimetric measurement domains. The condition of incoherence relates to the measurement process which, in a radar scenario, would imply designing an incoherent transmit waveform or an equivalent scanning strategy with an existing waveform. In this study, we formulate a sparse signal model for precipitation targets as observed by a polarimetric weather radar. The applicability of CS for such a signal model is then examined through simulations of incoherent measurements along with real weather data obtained from Iowa X-band Polarimetric (XPOL) radar units.
Robertson, Andrew W.
, Andrew W. Robertson, M. Neil Ward, Ousmane N'Diaye International Research Institute for Climate and Society, The Earth Institute at Columbia University Palisades, New York Submitted to Journal of Climate distribution of rainfall matches the observed one. The k nearest neighbor and weather classification schemes re
Wang, L.-P.; Ochoa-Rodríguez, S.; Onof, C.; Willems, P.
Gauge-based radar rainfall adjustment techniques have been widely used to improve the applicability of radar rainfall estimates to large-scale hydrological modelling. However, their use for urban hydrological applications is limited as they were mostly developed based upon Gaussian approximations and therefore tend to smooth off so-called "singularities" (features of a non-Gaussian field) that can be observed in the fine-scale rainfall structure. Overlooking the singularities could be critical, given that their distribution is highly consistent with that of local extreme magnitudes. This deficiency may cause large errors in the subsequent urban hydrological modelling. To address this limitation and improve the applicability of adjustment techniques at urban scales, a method is proposed herein which incorporates a local singularity analysis into existing adjustment techniques and allows the preservation of the singularity structures throughout the adjustment process. In this paper the proposed singularity analysis is incorporated into the Bayesian merging technique and the performance of the resulting singularity-sensitive method is compared with that of the original Bayesian (non singularity-sensitive) technique and the commonly-used mean field bias adjustment. This test is conducted using as case study four storm events observed in the Portobello catchment (53 km2) (Edinburgh, UK) during 2011 and for which radar estimates, dense rain gauge and sewer flow records, as well as a recently-calibrated urban drainage model were available. The results suggest that, in general, the proposed singularity-sensitive method can effectively preserve the non-normality in local rainfall structure, while retaining the ability of the original adjustment techniques to generate nearly unbiased estimates. Moreover, the ability of the singularity-sensitive technique to preserve the non-normality in rainfall estimates often leads to better reproduction of the urban drainage system's dynamics, particularly of peak runoff flows.
Rosenfeld, Daniel; Amitai, Eyal; Wolff, David B.
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.
Bachmann, Svetlana Monakhova
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.
Nayak, Munir Ahmad; Ghosh, Subimal
A major component of flood alert broadcasting is the short-term prediction of extreme rainfall events, which remains a challenging task, even with the improvements of numerical weather prediction models. Such prediction is a high priority research challenge, specifically in highly urbanized areas like Mumbai, India, which is extremely prone to urban flooding. Here, we attempt to develop an algorithm based on a machine learning technique, support vector machine (SVM), to predict extreme rainfall with a lead time of 6-48 h in Mumbai, using mesoscale (20-200 km) and synoptic scale (200-2,000 km) weather patterns. The underlying hypothesis behind this algorithm is that the weather patterns before (6-48 h) extreme events are significantly different from those of normal weather days. The present algorithm attempts to identify those specific patterns for extreme events and applies SVM-based classifiers for extreme rainfall classification and prediction. Here, we develop the anomaly frequency method (AFM), where the predictors (and their patterns) for SVM are identified with the frequency of high anomaly values of weather variables at different pressure levels, which are present before extreme events, but absent for non-extreme conditions. We observe that weather patterns before the extreme rainfall events during nighttime (1800 to 0600Z) is different from those during daytime (0600 to 1800Z) and, accordingly, we develop a two-phase support vector classifier for extreme prediction. Though there are false alarms associated with this prediction method, the model predicts all the extreme events well in advance. The performance is compared with the state-of-the-art statistical technique fingerprinting approach and is observed to be better in terms of false alarm and prediction.
Roberto, N.; Baldini, L.; Facheris, L.; Chandrasekar, V.
Several satellite missions employing X-band synthetic aperture radar (SAR) have been activated to provide high-resolution images of normalized radar cross-sections (NRCS) on land and ocean for numerous applications. Rainfall and wind affect the sea surface roughness and consequently the NRCS from the combined effects of corrugation due to impinging raindrops and surface wind. X-band frequencies are sensitive to precipitation: intense convective cells result in irregularly bright and dark patches in SAR images, masking changes in surface NRCS. Several works have modeled SAR images of intense precipitation over land; less adequately investigated is the precipitation effect over the sea surface. These images are analyzed in this study by modeling both the scattering and attenuation of radiation by hydrometeors in the rain cells and the NRCS surface changes using weather radar precipitation estimates as input. The reconstruction of X-band SAR returns in precipitating clouds is obtained by the joint utilization of volume reflectivity and attenuation, the latter estimated by coupling ground-based radar measurements and an electromagnetic model to predict the sea surface NRCS. Radar signatures of rain cells were investigated using X-band SAR images collected from the COSMO-SkyMed constellation of the Italian Space Agency. Two case studies were analyzed. The first occurred over the sea off the coast of Louisiana (USA) in summer 2010 with COSMO-SkyMed (CSK®) ScanSar mode monitoring of the Deepwater Horizon oil spill. Simultaneously, the NEXRAD S-band Doppler radar (KLIX) located in New Orleans was scanning the same portion of ocean. The second case study occurred in Liguria (Italy) on November 4, 2011, during an extraordinary flood event. The same events were observed by the Bric della Croce C-band dual polarization radar located close to Turin (Italy). The polarimetric capability of the ground radars utilized allows discrimination of the composition of the precipitation volume, in particular distinguishing ice from rain. Results shows that for space-borne SAR at X-band, effects due to precipitation on water surfaces can be modeled using coincident ground-based weather radar measurements.
Curry, Robert Gene
A STUDY OF THE APPLICABILITY OF WEATHER RADAR IN STREAMFLOW FORECASTING A Thesi. s Robert Gene Curry Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirement for the degree of MASTER OF SCIENCE... August 1970 Major Subject: Meteorology A STUDY OP THE APPLICASILITY OF WEATHER RADAR IN STREAHPLOW FORECASTING A Thesis Robert Gene Curry Approved as to style snd oontent by: (Chairman of Corned. ttee) (Head of Depar t) (Hember) (Member) August...
M. Kitchen; P. M. Jackson
A large set of high-vertical-resolution reflectivity profiles was used to simulate the performance of radars in the United Kingdom weather radar network. In particular, limitations in the estimation of surface precipitation due to incomplete beam filling and variability in the reflectivity profile were investigated. Marked seasonal variations in range performance were found and detection failures were shown to make a
O?ródka, K.; Szturc, J.
Weather radar data volumes are commonly processed to obtain various 2-D Cartesian products based on the transfer from polar to Cartesian representations through a certain interpolation method. In this research, an algorithm of the spatial interpolation of polar reflectivity data with respect to QI (quality index) data is applied to find the Cartesian reflectivity as PPI (plan position indicator) product and generate a corresponding QI field. On this basis, quality-based versions of standard algorithms for the generation of the following products have been developed: ETOP (echo top), MAX (maximum of reflectivity), and VIL (vertically integrated liquid water). Moreover, as an example of a higher-level product, a CONVECTION (detection of convection) has been defined as a specific combination of the above-listed standard products. A corresponding QI field is determined for each generated product, taking into account the quality of the pixels from which a given product was determined and how large a fraction of the investigated heights was scanned. Examples of such quality-based products are presented in the paper.
Robertson, Franklin R.; Fitzjarrald, Dan E.; Kummerow, Christian D.
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.
Mandapaka, P. V.; Krajewski, W. F.; Mantilla, R.; Gupta, V. K.
Idealized model studies have shown that space-time rainfall intermittency and its statistical scaling properties have a significant impact on statistical scaling of flood peaks with respect to drainage area. In this study, simulation is used as a methodological tool to explore the effects of radar-rainfall uncertainties on the observed scaling of flood peaks. Simulated rainfall fields with varying power spectrum and advection velocities are corrupted with an error structure based on substantial empirical evidence to mimic the radar-based estimates. The scaling properties of peak discharges are then obtained for the 1100 km2 Whitewater basin in Kansas, U.S. using the error-corrupted rainfall fields. A hillslope and channel link based GIS simulation environment called CUENCAS is used to simulate flood peaks from physical processes, and to investigate the effects of radar- rainfall errors on the scaling in floods. The parameters for the rainfall model are obtained by analyzing customized high-resolution radar-rainfall products based on NEXRAD Level II data for Kansas.
In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in the radar line of sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on 6 years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. It is shown that this in part can be explained by detection by the radar sidelobes and by scattering off increased levels of dust and turbulence. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. It is shown that, when weather echoes give rise to higher reflectivity values than those of the wind farm, the negative impact of the wind turbines is greatly reduced for all spectral moments.
In many countries wind turbines are rapidly growing in numbers as the demand for energy from renewable sources increases. The continued deployment of wind turbines can, however, be problematic for many radar systems, which are easily disturbed by turbines located in radar line-of-sight. Wind turbines situated in the vicinity of Doppler weather radars can lead to erroneous precipitation estimates as well as to inaccurate wind- and turbulence measurements. This paper presents a quantitative analysis of the impact of a wind farm, located in southeastern Sweden, on measurements from a nearby Doppler weather radar. The analysis is based on six years of operational radar data. In order to evaluate the impact of the wind farm, average values of all three spectral moments (the radar reflectivity factor, absolute radial velocity, and spectrum width) of the nearby Doppler weather radar were calculated, using data before and after the construction of the wind farm. It is shown that all spectral moments, from a large area at and downrange from the wind farm, were impacted by the wind turbines. It was also found that data from radar cells far above the wind farm (near 3 km altitude) were affected by the wind farm. We show that this is partly explained by changes in the atmospheric refractive index, bending the radar beams closer to the ground. In a detailed analysis, using data from a single radar cell, frequency distributions of all spectral moments were used to study the competition between the weather signal and wind turbine clutter. We show that when weather echoes give rise to higher reflectivity values than that of the wind farm, the negative impact of the wind turbines disappears for all spectral moments.
Berenguer, M.; Sempere-Torres, D.; Hürlimann, M.
This work presents a technique for debris-flow (DF) forecasting able to be used in the framework of DF early warning systems at regional scale. The developed system is applied at subbasin scale and is based on the concepts of fuzzy logic to combine two ingredients: (i) DF subbasin susceptibility assessment based on geomorphological variables and (ii) the magnitude of the rainfall situation as depicted from radar rainfall estimates. The output of the developed technique is a three-class warning ("low", "moderate" or "high") in each subbasin when a new radar rainfall map is available. The developed technique has been applied in a domain in the eastern Pyrenees (Spain) from May to October 2010. The warning level stayed "low" during the entire period in 20% of the subbasins, while in the most susceptible subbasins the warning level was at least "moderate" for up to 10 days. Quantitative evaluation of the warning level was possible in a subbasin where debris flows were monitored during the analysis period. The technique was able to identify the three events observed in the catchment (one debris flow and two hyperconcentrated flow events) and produced no false alarm.
Massachusetts at Amherst, University of
Multiagent Meta-level Control for a Network of Weather Radars Shanjun Cheng, Anita Raja Department-level control significantly improves the performance of the tornado tracking network for a variety of weather of multiagent systems. In this paper, we argue that multiagent meta-level control is an effective way
Sutherland-Stacey, Luke; Shucksmith, Paul; Austin, Geoff
The Atmospheric Physics Group runs a number of high resolution X-band mobile rain radars. The radars are unusual in that they operate at very high spatial and temporal resolution but short range (100m/20sec/20km) as compared with the C-band radars of the New Zealand Meteorological Service (2km/7min/240km). Portability was a key design criterion for the radars, which can either be towed by a personal four wheel drive vehicle or carted by a container truck. Past deployments include the slopes of an erupting volcano, the path of a tropical storm and overwintering in a mountain range. It is well known that sampling and representativeness problems associated with sparse gauge networks and C-band radars can result in high uncertainty in estimates of aerial rainfall. Some of this error is associated with poor sampling of the spatial and temporal scales which are important to precipitation processes. In the case of long range radar, the beam height increase with range also introduces uncertainty when trying to infer precipitation at the ground, even after reflectivity profile correction methods are applied. This paper describes a recently completed field campaign in a hydro power catchment in the North Island of New Zealand. The radar was deployed in a pasture on a farm overlooking the catchment which is about 15km x 10km in size. The catchment is about 150km from the nearest national C-band radar. A number of rain gauges, including high resolution drop counters, were deployed nearby. X-band and comparative C-band radar observations of particular events including orographically initiated convection, frontal systems and widespread rain types are presented. The convective events are characterised by short length scales and rapid evolution, but even the widespread rain has embedded structure. The observations indicate that the evolution time and spatial scales associated with many of the hydrometeors observed in this work precludes aerial estimates being made with sparse gauge networks. Due to the relatively long range and lower spatial and temporal resolution the C-band images contained less information than X-band scans of the same hydrometeors. On the other hand, per event statistics indicate that the majority of variance in rain gauge measurements can be explained from the co-located X-band radar pixel. Quantitative retrieval of accumulation was possible out to about 15km range after applying range and bias correction.
Fumie A. Furuzawa; Kenji Nakamura
It is well known that precipitation rate estimation is poor over land. Using the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI), the performance of the TMI rain estimation was investigated. Their differences over land were checked by using the orbit-by-orbit data for June 1998, December 1998, January 1999, and February 1999, and the following
Smith, G. D.
/acts Heteorologp THH CSE Oy COHPOSZTH ueAH PauZOnueaS II ITIOPTZC II@XIII kIkLYS1$ Approved aa ro eryia aad coaraat bye Cha of Coiaeitres Head of Baparensnt The uss of radar see?her observations in analysis of w*nther charts is considered. Thats observations... sre in the form of composite : radar PPZ photographs . . =. k= symbology is. suggested for ds~ioting the gross features of the radar precipitation echoee. The symbology can be used to indicate echo analysis of PPX photographs and to plo? radar data...
Liberman, Y.; Samuels, R.; Alpert, P.; Messer, H.
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.
Marzano, F. S.; Mori, S.; Mugnai, A.; Weinman, J. A.
Climate modelers need global precipitation measurements because the released latent heat distribution has a profound effect on the performance of such models. Precipitation measurements are also required to facilitate water management strategies by hydrologists, and managers of transportation, agricultural and flood relief agencies. Although precipitation measurements are widely available in technologically advanced countries, the measurement of precipitation over oceans, mountainous terrain and less developed regions leaves much to be desired. Since the 1980s much of our understanding of global precipitation has been provided by space-borne passive microwave radiometers and a combination of microwave and infrared passive measurements. Unfortunately space-borne microwave radiometers, even in combination with infrared sensors, have had limited success in retrieving precipitation over land because they rely heavily on the scattering properties of ice in the upper regions of precipitating clouds. Those scattering properties may be poorly related to surface rainfall rates. This limitation can be overcome over land by space-based radars operating at X or Ku band. The Ku band Precipitation Radar (PR) aboard the Tropical Rainfall Measurement Mission (TRMM) program has provided unique precipitation measurements over land. Mountainous terrain has presented challenges to both ground and space-based radars. Radar reflectivity measurements from PR are routinely removed within about 1 to 2 kilometers from mountainous surfaces to avoid ground clutter. If significant shallow precipitation or rain cells smaller than the 4 km horizontal resolution occur along mountain slopes, then such precipitation may be missed by PR. The measurement of light, small rain cells may also be impaired by the signal-to-noise ratio floor of the PR. A new opportunity to measure precipitation from space may be afforded by the forthcoming availability of several X-band Synthetic Aperture Radars (X-SARs). The TerraSAR-X (TSX) was launched on June 15, 2007 by the Deutsches Zentrum f. Luft u. Raumfahrt (DLR) and another X-SAR will be launched by 2009. The Constellation of Small Satellites for Mediterranean basin Observations (COSMO-SkyMed, CSK) will be launched by the Agenzia Spaziale Italiana (ASI) within 2009. The first of four of these satellites was launched by ASI on June 7, 2007. The Israeli Defense Ministry plans to launch yet another X-band SAR, the TecSAR SAR Technology Demonstration Satellite, later in 2009. Space-borne X-SARs are generally not designed for atmospheric observation. SARs are often considered "all weather" sensors. However, there is relevant theoretical and experimental evidence that X-band radar may be significantly affected by precipitation occurrence within the synthetically scanned area -. As a matter of fact, PR was designed at Ku band which is only 4 GHz away from X band. Several authors showed that X-SARs are more sensitive to rainfall effects than SARs operating at longer wavelengths, such as L and C bands -. For example, this was demonstrated by the Shuttle Missions STS-59 and 68 of 1994 and the STS-99 Shuttle Radar Topography Mission (SRTM) of 2000 carrying the first X-SAR along with L and C band SARs. Rainfall reflectivity at X-band may be enhanced by about 12 dB and the attenuation increased by about 4 dB when compared to C-band reflectivity and attenuation. The potential of X-SAR for precipitation retrieval is intriguing. They will probably be able to measure rainfall over land with greater sensitivity than from radiometers. The high spatial resolution (less than 100 m) of X-SARs can provide new insights into the structure of precipitating clouds with respect to PR and its future upgrades. X-SAR platforms could also significantly enhance the planned constellation of satellites carrying microwave radiometers and radars that will be part of the foreseen Global Precipitation Measurements (GPM) mission. These X-SAR satellites, then, may make a valuable contribution to our understanding of the hydrological
Gooré Bi, Eustache; Monette, Frédéric; Gasperi, Johnny
Urban rainfall runoff has been a topic of increasing importance over the past years, a result of both the increase in impervious land area arising from constant urban growth and the effects of climate change on urban drainage. The main goal of the present study is to assess and analyze the correlations between rainfall variables and common indicators of urban water quality, namely event mean concentrations (EMCs) and event fluxes (EFs), in order to identify and explain the impacts of each of the main rainfall variables on the generation process of urban pollutants during wet periods. To perform this analysis, runoff from eight summer rainfall events that resulted in combined sewer overflow (CSO) was sampled simultaneously from two distinct catchment areas in order to quantify discharges at the respective outfalls. Pearson statistical analysis of total suspended solids (TSS), chemical oxygen demand (COD), carbonaceous biochemical oxygen demand at 5 days (CBOD5), total phosphorus (Ptot) and total kedjal nitrogen (N-TKN) showed significant correlations (? = 0.05) between dry antecedent time (DAT) and EMCs on one hand, and between total rainfall (TR) and the volume discharged (VD) during EFs, on the other. These results show that individual rainfall variables strongly affect either EMCs or EFs and are good predictors to consider when selecting variables for statistical modeling of urban runoff quality. The results also show that in a combined sewer network, there is a linear relationship between TSS event fluxes and COD, CBOD5, Ptot, and N-TKN event fluxes; this explains 97% of the variability of these pollutants which adsorb onto TSS during wet weather, which therefore act as tracers. Consequently, the technological solution selected for TSS removal will also lead to a reduction of these pollutants. Given the huge volumes involved, urban runoffs contribute substantially to pollutant levels in receiving water bodies, a situation which, in a climate change context, may get much worse as a result of more frequent, shorter, but more intense rainfall events.
Abhilash, S.; Sahai, A. K.; Mohankumar, K.; George, John P.; Das, Someshwar
In this paper the impact of Doppler weather radar (DWR) reflectivity and radial velocity observations for the short range forecasting of a tropical storm and associated rainfall event have been examined. Doppler radar observations of a tropical storm case that occurred during 29-30 October 2006 from SHARDWR (13.6° N, 80.2° E) are assimilated in the WRF 3DVAR system. The observation operator for radar reflectivity and radial velocity is included within latest version of WRF 3DVAR system. Keeping all model physics the same, three experiments were conducted at a horizontal resolution of 30 km. In the control experiment (CTRL), NCEP Final Analysis (FNL) interpolated to the model grid was used as the initial condition for 48-h free forecast. In the second experiment (NODWR), 6-h assimilation cycles have been carried out using all conventional (radiosonde and surface data) and non-conventional (satellite) observations from the Global Telecommunication System (GTS). The third experiment (DWR) is the same as the second, except Doppler radar radial velocity and reflectivity observations are also used in the assimilation cycle. Continuous 6-h assimilation cycle employed in the WRF-3DVAR system shows positive impact on the rainfall forecast. Assimilation of DWR data creates several small scale features near the storm centre. Additional sensitivity experiments were conducted to study the individual impact of reflectivity and radial velocity in the assimilation cycle. Radar data assimilation with reflectivity alone produced large analysis response on both thermodynamical and dynamical fields. However, radial velocity assimilation impacted only on dynamical fields. Analysis increments with radar reflectivity and radial velocity produce adjustments in both dynamical and thermodynamical fields. Verification of QPF skill shows that radar data assimilation has a considerable impact on the short range precipitation forecast. Improvement of the QPF skill with radar data assimilation is more clearly seen in the heavy rainfall (for thresholds >7 mm) event than light rainfall (for thresholds of 1 and 3 mm). The spatial pattern of rainfall is well simulated by the DWR experiment and is comparable to TRMM observations.
Shepherd, J. Marshell; Starr, David OC. (Technical Monitor)
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.
Jameson, A. R.
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.
Liberman, Y.; Samuels, R.; Alpert, P.; Messer, H.
One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date the most effective methods for large scale rainfall estimates are radar, satellites, and more recently, received signal level (RSL) measurements received from commercial microwave networks (CMN). While these methods provide improved spatial resolution over traditional rain gauges, these have their limitations as well. For example, the wireless CMN, which are comprised of microwave links (ML), are dependant upon existing infrastructure, and the ML arbitrary distribution in space. Radar, on the other hand, is known in its limitation in accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rain fall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that by using the proposed new method we not only generate a more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show an improvement of rain rate estimation over CMN or radar alone, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, and the accurate rainfall measurements over large areas at sub-hourly time scales, will allow for improved understanding, initialization and calibration of hydrological and meteorological models necessary, mainly, for water resource management and planning.
Elshamy, Mohamed Ezzat; Wheater, Howard S.; Gedney, Nicola; Huntingford, Chris
Hydrological impacts of climate change are frequently assessed by off-line forcing of a hydrological model with climatic scenarios from either Global Circulation Models (GCMs) or simpler analogue models. Most hydrological models require a daily time step or smaller while observed climatology and GCM and analogue model output is generally available on a monthly time step. This study investigates and improves a rainfall disaggregation model currently used to convert monthly rainfall totals down to the daily time step. The performance of the model is evaluated using daily data from a network of raingauges covering the Nile basin and contrasted with data from a relatively dense raingauge network from the Blackwater Catchment, in the Southeast of the UK. Whilst the model preserves the mean properties of rainfall occurrence and depth, there is significant overestimation of rainfall variability. Regional calibration and better formulation of the generator improve simulation of variability as well as other aspects of rainfall properties. Hence the parameters required by the weather generator model cannot be regarded as universal. Proportional correction of daily amounts is applied to insure that monthly totals are preserved, allowing retention of interannual variability, and this was shown to have little effect on the distribution of wet day amounts. The calibration of parameter estimation equations has investigated spatial dependence of climate variables and parameters and found that (as expected) rainfall properties exhibit scale-dependence, which may be utilized to transfer data from one spatial scale to another. In order to complete the framework, a model is developed to estimate the wet fraction from monthly total when the former is not available.
Chikamori, Hidetaka; Nagai, Akihiro
This paper presents the estimation procedure of a flood envelope curve originally developed by Kadoya and Nagai (1979) on the basis of depth-area-duration (DAD) analysis of radar precipitation data in order to examine the availability of spatial distribution data of precipitation for statistical flood peak analysis. The estimated flood envelope curves by applying the presented procedure to the Yoshii River Basin located in Okayama Prefecture of the western Japan well enveloped the flood peaks observed in the Hiroshima and Okayama Prefectures; the curves tended, however, to overestimate flood peaks for small catchments. It was explained by the fact that very limited areas are with regionally maximum areal rainfall arising maximum flood peak discharge and the other areas are with smaller areal rainfall than maximum in the objective region. Flood envelope curve equation considering spatial probability of regionally maximum areal rainfall was presented and applied to the Yoshii River Basin to show the effect of adjusting the spatial probability for mitigating overestimation of maximum flood peaks for small basin. This result shows probabilistic aspects of flood envelope curves deterministically estimated from hydrological records, which should be considered when determining design flood discharge for dam planning.
Borga, M.; Creutin, J. D.
Flood risk mitigation is accomplished through managing either or both the hazard and vulnerability. Flood hazard may be reduced through structural measures which alter the frequency of flood levels in the area. The vulnerability of a community to flood loss can be mitigated through changing or regulating land use and through flood warning and effective emergency response. When dealing with flash-flood hazard, it is gener- ally accepted that the most effective way (and in many instances the only affordable in a sustainable perspective) to mitigate the risk is by reducing the vulnerability of the involved communities, in particular by implementing flood warning systems and community self-help programs. However, both the inherent characteristics of the at- mospheric and hydrologic processes involved in flash-flooding and the changing soci- etal needs provide a tremendous challenge to traditional flood forecasting and warning concepts. In fact, the targets of these systems are traditionally localised like urbanised sectors or hydraulic structures. Given the small spatial scale that characterises flash floods and the development of dispersed urbanisation, transportation, green tourism and water sports, human lives and property are exposed to flash flood risk in a scat- tered manner. This must be taken into consideration in flash flood warning strategies and the investigated region should be considered as a whole and every section of the drainage network as a potential target for hydrological warnings. Radar technology offers the potential to provide information describing rain intensities almost contin- uously in time and space. Recent research results indicate that coupling radar infor- mation to distributed hydrologic modelling can provide hydrologic forecasts at all potentially flooded points of a region. Nevertheless, very few flood warning services use radar data more than on a qualitative basis. After a short review of current under- standing in this area, two issues are examined: advantages and caveats of using radar rainfall estimates in operational flash flood forecasting, methodological problems as- sociated to the use of hydrological models for distributed flash flood forecasting with rainfall input estimated from radar.
of light by small particles, 1983 4. H.C. van de Hulst: Light Scattering by Small Particles, 1981, 1957 #12 Radar: Principle and applications, 2001 3. C.E. Bohren and D.R. Huffman: Absorption and scattering
Guenzi, Diego; Bechini, Renzo; Boraso, Rodolfo; Cremonini, Roberto; Fratianni, Simona
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.
Angulo, I.; Grande, O.; Jenn, D.; Guerra, D.; de la Vega, D.
The World Meteorological Organization (WMO) has repeatedly expressed concern over the increasing number of impact cases of wind turbine farms on weather radars. Since nowadays signal processing techniques to mitigate Wind Turbine Clutter (WTC) are scarce, the most practical approach to this issue is the assessment of the potential interference from a wind farm before it is installed. To do so, and in order to obtain a WTC reflectivity model, it is crucial to estimate the Radar Cross Section (RCS) of the wind turbines to be built, which represents the power percentage of the radar signal that is backscattered to the radar receiver. This paper first characterizes the RCS of wind turbines in the weather radar frequency bands by means of computer simulations based on the Physical Optics theory, and then proposes a simplified model to estimate wind turbine RCS values. This model is of great help in the evaluation of the potential impact of a certain wind farm on the weather radar operation.
Gauthreaux, Sidney A; Livingston, John W; Belser, Carroll G
Organisms in the aerosphere have been detected by radar since its development in the 1940s. The national network of Doppler weather radars (WSR-88D) in the United States can readily detect birds, bats, and insects aloft. Level-II data from the radar contain information on the reflectivity and radial velocity of targets and on width of the spectrum (SD of radial velocities in a radar pulse volume). Information on reflectivity can be used to quantify density of organisms aloft and radial velocity can be used to discriminate different types of targets based on their air speeds. Spectral width can also provide some useful information when organisms with very different air speeds are aloft. Recent work with dual-polarization radar suggests that it may be useful for discriminating birds from insects in the aerosphere, but more development and biological validation are required. PMID:21669769
Shepherd, J. Marshall; Pierce, Harold; Starr, David OC. (Technical Monitor)
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.
Using MSG-SEVIRI Cloud Physical Properties and Weather Radar Observations for the Detection of Cb (SEVIRI) on board Meteosat Second Generation (MSG) satellites and weather radar reflectivity factors/TCu clouds for the collection of pixels that pass the CCM. In this model, MSG-SEVIRI cloud physical
Reading, University of
Weather Radar and Hydrology (Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ.firstname.lastname@example.org 2 Met Office, Exeter,UK Abstract Several radar parameters quantifying signal variability in single-polarisation radar measurements (Power Ratio, PR; Clutter Phase Alignment, CPA; and Absolute Power Difference, APD
Reading, University of
(experienced by radars with magnetron transmitters) during the time taken for Doppler #12;Nicol et al.2Weather Radar and Hydrology (Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ. 3XX, 2011). Copyright 2011 IAHS Press 1 Operational Radar Refractivity Retrieval for Numerical
Lavers, David A.; Villarini, Gabriele
9-16 September 2013 significant portions of Colorado experienced extreme precipitation and flooding resulting in large socioeconomic damages and fatalities. Here we investigate the ability of eight global state-of-the-art numerical weather prediction systems to forecast rainfall during the event. Forecasts were analyzed from initializations at 12 UTC 5 September to 12 UTC 12 September to determine when, and how well, the event was captured. Ensemble mean rainfall patterns initialized on 5 September (roughly 4+ day lead time) did not forecast the event's persistent nature; conversely, forecasts initialized on 9 September captured the rainfall patterns reasonably well, although with incorrect rainfall values. Accumulated rainfall forecasts improved when the region considered increased from a 0.5° area centered over Boulder to the entire state of Colorado. We conclude that the models provided guidance indicating a significant period of rainfall in Colorado from 9 September 2013, although not necessarily in the correct locations.
Wagner, A.; Seltmann, J.; Kunstmann, H.
A radar-based rainfall statistic demands high quality data that provide realistic precipitation amounts in space and time. Instead of correcting single radar images, we developed a post-correction scheme for long-term composite radar data that corrects corrupted areas, but preserves the original precipitation patterns. The post-correction scheme is based on a 5 year statistical analysis of radar composite data and its constituents. The accumulation of radar images reveals artificial effects that are not visible in the individual radar images. Some of them are already inherent to single radar data such as the effect of increasing beam height, beam blockage or clutter remnants. More artificial effects are introduced in the process of compositing such as sharp gradients at the boundaries of overlapping areas due to different beam heights and resolution. The cause of these disturbances, their behaviour with respect to reflectivity level, season or altitude is analysed based on time-series of two radar products: the single radar reflectivity product PX for each of the 16 radar systems of the German Meteorological Service (DWD) for the time span 2000 to 2006 and the radar composite product RX of DWD from 2005 through to 2009. These statistics result in additional quality information on radar data that is not available elsewhere. The resulting robust characteristics of disturbances, e.g. the dependency of the frequencies of occurrence of radar reflectivities on beam height, are then used as a basis for the post-correction algorithm. The scheme comprises corrections for shading effects and speckles, such as clutter remnants or overfiltering, as well as for systematic differences in frequencies of occurrence of radar reflectivities between the near and the far ranges of individual radar sites. An adjustment to rain gauges is also included. Applying this correction, the Root-Mean-Square-Error for the comparison of radar derived annual rain amounts with rain gauge data decreases from 1181 to 171 mm a-1 (application period: 2005, 2006 and 2009) and from 317 to 178 mm a-1 (validation period: 2007, 2008). The entire correction scheme is applicable on an annual scale. The correction of mean annual rain amounts derived from radar composite data for the whole period leads to an almost undisturbed and homogeneous distribution of rain amounts for Germany.
Bharadwaj, Nitin; Chandrasekar, V.
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.
Fries, Marc; Matson, Robert; Schaefer, Jacob; Fries, Jeffery; Hankey, Mike; Anderson, Lindsay
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 . Arguably, the meteorites recovered via these methods are of special scientific value as they are relatively unweathered, fresh falls. To illustrate this, a recent SAO/NASA ADS search using the keyword "meteorite" shows that all 50 of the top search results included at least one named meteorite recovered from a meteorite fall. This is true even though only 1260 named meteorite falls are recorded among the >49,000 individual falls recorded in the Meteoritical Society online database. The US NEXRAD system used thus far to locate meteorite falls covers most of the United States' surface area. Using a WMO map of the world's weather radars, we estimate that the total coverage of the other 75 national weather radar networks equals about 3.6x NEXRAD's coverage area. There are two findings to draw from this calculation: 1) For the past 16 years during which 18 falls are seen in US radar data, there should be an additional 65 meteorite falls recorded in worldwide radar imagery. Also: 2) if all of the world's radar data could be analyzed, the rate of recovery of fresh meteorite falls can increase by as much as 3.6x the current rate. The authors' experience to date indicates that the most effective course of action would be to have local meteorite research groups (outside of the US) form research consortia and develop a working relationship with their nation's weather bureau for access to data. These research consortia could utilize the same, proven methods used for US NEXRAD imagery, internet eyewitness report aggregation, seismometry analysis, etc. to locate meteorite falls. The consortia could then recover and analyze meteorite falls and enrich their own research efforts. It would be beneficial to conduct a global program to coordinate the development of methods and data tools, as well as to coordinate meteorite sample sharing and research. Perhaps an institution such as the Meteoritical Society could lead such an effort.
Turso, S.; Paolella, S.; Gabella, M.; Perona, G.
In this paper, MicroRadarNet, a novel micro radar network for continuous, unattended meteorological monitoring is presented. Key aspects and constraints are introduced. Specific design strategies are highlighted, leading to the technological implementations of this wireless, low-cost, low power consumption sensor network. Raw spatial and temporal datasets are processed on-board in real-time, featuring a consistent evaluation of the signals from the sensors and optimizing the data loads to be transmitted. Network servers perform the final post-elaboration steps on the data streams coming from each unit. Final network products are meteorological mappings of weather events, monitored with high spatial and temporal resolution, and lastly served to the end user through any Web browser. This networked approach is shown to imply a sensible reduction of the overall operational costs, including management and maintenance aspects, if compared to the traditional long range monitoring strategy. Adoption of the TITAN storm identification and nowcasting engine is also here evaluated for in-loop integration within the MicroRadarNet data processing chain. A brief description of the engine workflow is provided, to present preliminary feasibility results and performance estimates. The outcomes were not so predictable, taking into account relevant operational differences between a Western Alps micro radar scenario and the long range radar context in the Denver region of Colorado. Finally, positive results from a set of case studies are discussed, motivating further refinements and integration activities.
Carey, L. D.; Cifelli, R.; Petersen, W. A.; Rutledge, S. A.
The Tropical Rainfall Measuring Mission (TRMM) is a NASA satellite project initiated to address a gap in our ability to accurately observe detailed rainfall patterns over the tropical continents and oceans. To support TRMM, several field campaigns were conducted. The TRMM-LBA (Large-scale Biosphere Atmosphere) experiment was conducted over the southwestern region of the Amazon (state of Rondonia, Brazil) in order to provide detailed information on the precipitation characteristics in the interior of a tropical continent. Information from TRMM-LBA will be used for validation of TRMM satellite products and for initialization and validation of cloud-resolving models and passive microwave retrieval algorithms. During the TRMM-LBA field campaign, a variety of instrumentation was deployed during the wet season (January - February 1999) to measure rainfall including several rain gauge networks, disdrometers, and the S-band polarimetric (NCAR S-POL) research radar. The focus of this study will be on the estimation, validation, and uncertainty of rain rate estimates derived from the NCAR S-POL radar. The S-POL data were carefully corrected for the presence of clear-air echo, ground clutter, anomalous propagation, partial beam blocking, precipitation attenuation, and calibration biases by applying polarimetric radar methods. Using an optimal polarimetric radar technique, maps of rain rate have been calculated from observations of S-POL horizontal reflectivity (Zh), differential reflectivity (Zdr), and specific differential phase (Kdp) every ten minutes from 10 January to 28 February 1999. From these rain rate estimates, daily and 30-day rain accumulation maps have been compiled. When validated against the rain gauge totals, preliminary S-POL estimates of monthly rainfall, which utilized the equilibrium raindrop shape model of Beard and Chuang (1987), have a negative bias error in the range of -5% to -11% and a standard error of 14% to 20%. We will compare these results with the methodology of Gorgucci et al. (2000, 2001), which attempts to account for the variability in the raindrop shape-size relation. Some practical issues involved in the implementation of this method will be discussed. Finally, we will present preliminary attempts to estimate the uncertainty of the rain rates at each grid point following Bringi and Chandrasekar (2001, Ch. 8). As in BC2001, the uncertainty will be expressed as the standard deviation of R divided by R (? (R)/R). The uncertainty will be based on 1) the polarimetric algorithm and measurements utilized in the optimal rain rate approach at each point, 2) an estimate of error associated with measurement error as a function of rain rate, and 3) an estimate of the error associated with the utilized algorithm as a function of rain rate. Since there is inherent ambiguity in estimating uncertainty in this manner, we will also experiment with converting ? (R)/R into a qualitative uncertainty index (UI) ranging from 1 to 5, where 1 is very certain and 5 is very uncertain.
Ming Wei; Ben Niu; Wangping Xia; Yating Zhan
This work is the case study based on the remote sensing data about squall line in Shanghai at July 12 2004, focus on the analysis on Doppler radar echo products, satellite image, surface and sounding data, automatic weather station data. The purpose is to reveal the special structure of the squall line, recognize the evolution of strong convection with multi-scale
Kirsti Tellervo Jylha
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,
Derin, Yagmur; Anagnostou, Emmanouil; Kalogiros, John; Anagnostou, Marios
Accuracy and reliability of hydrological modeling studies heavily depends on quality and availability of precipitation estimates. Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements, such as those obtained during experimental studies with research radars. This study evaluates rainfall estimates from passive microwave (PMW) sensors onboard different earth orbiting platforms based on high spatial (150 m) and temporal (3 min) resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations during various field experiments in US and the Mediterranean region. The study first conducts independent error analysis of the XPOL precipitation estimates using independent in situ observations from rain gauges and disdrometers. Subsequently, coincident XPOL and PMW rainfall estimates are matched in space and time for a number of convective and stratiform type precipitation events. Standard GPROF PMW retrievals on SSM/I, TMI (2A12) and GPM-DPR observations are used to conduct the error analysis. All coincident XPOL data are extracted for the indicated overpasses to produce the satellite field-of-view averages for the orbital PMW sensor and produce match-ups of PMW/XPOL rainfall and raindrop size distribution parameters. In addition, gridded merged PMW datasets (MWCOMB, 3B40RT) that are used in most merged rainfall products are evaluated against the XPOL measurements. We will present error analysis results of PMW rainfall estimation and investigate dependences on precipitation type, vertical structure and precipitation microphysics (derived from XPOL).
Clementi, L.; Germann, U.; Panziera, L.
MeteoSwiss is currently developing a high spatial and temporal resolution, radar-based application to fulfill the need for immediate information on ongoing heavy rainfall occurring in small and remote catchments where no real-time rain gauge data are available. The tool is able to monitor in real time the precipitation accumulation over several time windows and it is adequate for widespread, orography forced precipitation. By means of a multiple criteria approach empirically adapted to the catchments, it automatically issues alerts valid for a 1 to 3 hours time frame. The goal of this application is to assist hydrologists and decision makers to answer in the very short term demanding questions in situations where it is not possible to wait for more precise information (models), or when better information is not available. The region crossed by the Emme river - a pre-alpine area on the northern slope of the Swiss Alps - showed to be very exposed to flood hazard during heavy rainfall periods (eg. 2005 and 2007) and therefore it is a good test bed for such application. Events of various magnitudes will be illustrated by means of qualitative and quantitative analysis and a first assessment of the tool based on the experiences gathered during summer 2009 will be presented.
Rozalis, S.; Price, C.; Yair, Y.; Morin, E.
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 these floods.
Debo Adeyewa, Z.; Nakamura, Kenji
The Global Precipitation Climatology Center global-precipitation-analyses rain gauge data have been used to validate the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) data over the major climatic regions in Africa. The threshold-matched precipitation index and the TRMM-and-other-sources `best-estimate' data (3B43) have also been compared with rain gauge data and with the TRMM PR rainfall product. In the 36-month climatological assessment of the satellite products at a grid spacing of 1.0°, continental Africa has been categorized into five distinct climatic regions: arid, semiarid, savanna, tropical wet, and the South Atlantic Ocean. Zonal mean analysis shows that TRMM PR has a large overestimation in the tropical-rain-forest region of Africa in December-January-February and in March-April-May. The bias is minimized in June-July-August and September-October-November. Bias is generally high for all algorithms in the dry seasons when rainfall is minimal but is less pronounced in the dry seasons of southern African climatic regions. In general, 3B43 has the closest agreement with rain gauge data. The derived standard errors of the algorithms in the climatic regions of Africa are used as a measure of reliability and show that quantitative climatological estimates of TRMM PR are reliable only in the wettest season of the northern savanna and southern semiarid regions when the mean precipitation is greater than 120 mm month-1. The study also shows that TRMM PR has the closest agreement with 3B43 over the South Atlantic Ocean. Over land, all the satellite estimates showed significant seasonally and regionally dependent bias.
Phillips, J. D.; Bull, J. S.; Hegarty, D. M.; Dugan, D. C.
In 1978 a joint NASA-FAA helicopter flight test was conducted to examine the use of weather-mapping radar for IFR guidance during landing approaches to oil rig helipads. The following navigation errors were measured: total system error, radar-range error, radar-bearing error, and flight technical error. Three problem areas were identified: (1) operational problems leading to pilot blunders, (2) poor navigation to the downwind final approach point, and (3) pure homing on final approach. Analysis of these problem areas suggests improvement in the radar equipment, approach procedure, and pilot training, and gives valuable insight into the development of future navigation aids to serve the off-shore oil industry.
Evans, James E.
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.
Alconis, Jenalyn; Eco, Rodrigo; Mahar Francisco Lagmay, Alfredo; Lester Saddi, Ivan; Mongaya, Candeze; Figueroa, Kathleen Gay
In response to the slew of disasters that devastates the Philippines on a regular basis, the national government put in place a program to address this problem. The Nationwide Operational Assessment of Hazards, or Project NOAH, consolidates the diverse scientific research being done and pushes the knowledge gained to the forefront of disaster risk reduction and management. Current activities of the project include installing rain gauges and water level sensors, conducting LIDAR surveys of critical river basins, geo-hazard mapping, and running information education campaigns. Approximately 700 automated weather stations and rain gauges installed in strategic locations in the Philippines hold the groundwork for the rainfall visualization system in the Project NOAH web portal at http://noah.dost.gov.ph. The system uses near real-time data from these stations installed in critical river basins. The sensors record the amount of rainfall in a particular area as point data updated every 10 to 15 minutes. The sensor sends the data to a central server either via GSM network or satellite data transfer for redundancy. The web portal displays the sensors as a placemarks layer on a map. When a placemark is clicked, it displays a graph of the rainfall data for the past 24 hours. The rainfall data is harvested by batch determined by a one-hour time frame. The program uses linear interpolation as the methodology implemented to visually represent a near real-time rainfall map. The algorithm allows very fast processing which is essential in near real-time systems. As more sensors are installed, precision is improved. This visualized dataset enables users to quickly discern where heavy rainfall is concentrated. It has proven invaluable on numerous occasions, such as last August 2013 when intense to torrential rains brought about by the enhanced Southwest Monsoon caused massive flooding in Metro Manila. Coupled with observations from Doppler imagery and water level sensors along the Marikina River, the local officials used this information and determined that the river would overflow in a few hours. It gave them a critical lead time to evacuate residents along the floodplain and no casualties were reported after the event.
Hou, Arthur; Zhang, Sara; Li, Jui-Lin; Reale, Oreste
Progress in understanding of the role of water in global weather and climate is currently limited by our knowledge of the spatial and temporal variability of primary hydrological fields such as precipitation and evaporation. The Tropical Rainfall Measuring Mission (TRMM) has recently demonstrated that use of microwave-based rainfall observations from space in data assimilation can provide better climate data sets and improve short-range weather forecasting. At NASA, we have been exploring non-traditional approaches to assimilating TRMM Microwave Imager (TMI) and Special Sensor Microwavehager (SSM/I) surface rain rate and latent heating profile information in global systems. In this talk we show that assimilating microwave rain rates using a continuous variational assimilation scheme based on moisture tendency corrections improves quantitative precipitation estimates (QPE) and related clouds, radiation energy fluxes, and large-scale circulations in the Goddard Earth Observing System (GEOS) reanalyses. Short-range forecasts initialized with these improved analyses also yield better QPE scores and storm track predictions for Hurricanes Bonnie and Floyd. We present a status report on current efforts to assimilate convective and stratiform latent heating profile information within the general variational framework of model parameter estimation to seek further improvements. Within the next 5 years, there will be a gradual increase in microwave rain products available from operational and research satellites, culminating to a target constellation of 9 satellites to provide global rain measurements every 3 hours with the proposed Global Precipitation Measurement (GPM) mission in 2007/2008. Based on what has been learned from TRMM, there is a high degree of confidence that these observations can play a'major role in improving weather forecasts and producing better global datasets for understanding the Earth's water and energy cycle. The key to success is to adopt an integrated approach to retrieval, validation, modeling, and data assimilation in a coordinated end-to-end observation-application program.
Roberto, N.; Baldini, L.; Gorgucci, E.; Facheris, L.; Chandrasekar, V.
Radar signatures of rain cells are investigated using X-band synthetic aperture radar (X-SAR) images acquired from COSMO-SkyMed constellation over oceans off the coast of Louisiana in summer 2010 provided by ASI archive. COSMO-SkyMed (CSK) monitoring of Deepwater Horizon oil spill provided a big amount of data during the period April-September 2010 and in July-August when several thunderstorms occurred in that area. In X-SAR images, radar signatures of rain cells over the sea usually consist of irregularly shaped bright and dark patches. These signatures originate from 1) the scattering and attenuation of radiation by hydrometers in the rain cells and 2) the modification of the sea roughness induced by the impact of raindrops and by wind gusts associated with rain cell. However, the interpretation of precipitation signatures in X-SAR images is not completely straightforward, especially over sea. Coincident measurements from ground based radars and an electromagnetic (EM) model predicting radar returns from the sea surface corrugated by rainfall are used to support the analysis. A dataset consisting of 4 CSK images has been collected over Gulf of Mexico while a WSR-88D NEXRAD S-band Doppler radar (KLIX) located in New Orleans was scanning the nearby portion of ocean. Terrestrial measurements have been used to reconstruct the component of X-SAR returns due to precipitation by modifying the known technique applied on measurements over land (Fritz et al. 2010, Baldini et al. 2011). Results confirm that the attenuation signature in X-SAR images collected over land, particularly pronounced in the presence of heavy precipitation cells, can be related to the S-band radar reflectivity integrated along the same path. The Normalized Radar Cross Section (NRCS) of land is considered to vary usually up to a few dBs in case of rain but with strong dependency on the specific type and conditions of land cover. While the NRCS of sea surface in clear weather condition can be considered as constant, in case of rain, at X-SAR incidence angles, it exhibits a dependence to precipitation event due the combined effects of corrugation due to the impinging raindrops and to the surface wind. Therefore, when retrieving of X-SAR NRCS in precipitation over the sea, this effect must be accounted for and can be quantified based on the precipitation event using a simple NRCS surface model. In this work, an EM model based on Bahar's Full Wave Model is used for evaluating such NRCS depending on polarization, frequency and incidence angle for different values of wind velocity and the root mean square height of the corrugation induced by rainfall. The reconstruction of X-SAR returns in precipitation is finally obtained by joint utilization of volume reflectivity and attenuation estimated from KLIX and the sea NRCS model.
Wang, Gaili; Wong, Wai-Kin; Hong, Yang; Liu, Liping; Dong, Jili; Xue, Ming
The primary objective of this study is to improve the performance of deterministic high resolution rainfall forecasts caused by severe storms by merging an extrapolation radar-based scheme with a storm-scale Numerical Weather Prediction (NWP) model. Effectiveness of Multi-scale Tracking and Forecasting Radar Echoes (MTaRE) model was compared with that of a storm-scale NWP model named Advanced Regional Prediction System (ARPS) for forecasting a violent tornado event that developed over parts of western and much of central Oklahoma on May 24, 2011. Then the bias corrections were performed to improve the forecast accuracy of ARPS forecasts. Finally, the corrected ARPS forecast and radar-based extrapolation were optimally merged by using a hyperbolic tangent weight scheme. The comparison of forecast skill between MTaRE and ARPS in high spatial resolution of 0.01° × 0.01° and high temporal resolution of 5 min showed that MTaRE outperformed ARPS in terms of index of agreement and mean absolute error (MAE). MTaRE had a better Critical Success Index (CSI) for less than 20-min lead times and was comparable to ARPS for 20- to 50-min lead times, while ARPS had a better CSI for more than 50-min lead times. Bias correction significantly improved ARPS forecasts in terms of MAE and index of agreement, although the CSI of corrected ARPS forecasts was similar to that of the uncorrected ARPS forecasts. Moreover, optimally merging results using hyperbolic tangent weight scheme further improved the forecast accuracy and became more stable.
Lengfeld, K.; Clemens, M.; Münster, H.; Ament, F.
This publication intends to prove that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) project observing precipitation with a temporal resolution of 30 s, a range resolution of 60 m and a sampling resolution of 1° in the azimuthal direction. The network covers an area of 60 km × 80 km. In this paper, algorithms used to obtain undisturbed precipitation fields from raw reflectivity data are described, and their performance is analysed. In order to correct operationally for background noise in reflectivity measurements, noise level estimates from the measured reflectivity field are combined with noise levels from the last 10 time steps. For detection of non-meteorological echoes, two different kinds of clutter algorithms are applied: single-radar algorithms and network-based algorithms. Besides well-established algorithms based on the texture of the logarithmic reflectivity field (TDBZ) or sign changes in the reflectivity gradient (SPIN), the advantage of the unique features of the high temporal and spatial resolution of the network is used for clutter detection. Overall, the network-based clutter algorithm works best with a detection rate of up to 70%, followed by the classic TDBZ filter using the texture of the logarithmic reflectivity field. A comparison of a reflectivity field from the PATTERN network with the product from a C-band radar operated by the German Meteorological Service indicates high spatial accordance of both systems in the geographical position of the rain event as well as reflectivity maxima. Long-term statistics from May to September 2013 prove very good accordance of the X-band radar of the network with C-band radar, but, especially at the border of precipitation events, higher-resolved X-band radar measurements provide more detailed information on precipitation structure because the 1 km range gate of C-band radars is only partially covered with rain. The standard deviation within a range gate of the C-band radar with a range resolution of 1 km is up to 3 dBZ at the borders of rain events. The probability of detection is at least 90%, the false alarm ratio less than 10% for both systems. Therefore, a network of high-resolution low-cost LAWRs can give valuable information on the small-scale structure of rain events in areas of special interest, e.g. urban regions, in addition to the nationwide radar networks.
Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko; ten Veldhuis, Marie-claire
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.
Mereu, Luigi; Silvio Marzano, Frank; Barsotti, Sara; Montopoli, Mario; Yeo, Richard; Arngrimsson, Hermann; Björnsson, Halldór; Bonadonna, Costanza
During an eruptive event the real-time forecasting of ash dispersal into the atmosphere is a key factor to prevent air traffic disasters. The ash plume is extremely hazardous to aircraft that inadvertently may fly through it. Real-time monitoring of such phenomena is crucial, particularly to obtain specific data for the initialization of eruption and dispersion models in terms of source parameters. The latter, such as plume height, ash concentration, mass flow rate and size spectra, are usually very difficult to measure or to estimate with a relatively good accuracy. Over the last years different techniques have been developed to improved ash plume detection and retrieval. Satellite-based observations, using multi-frequency visible and infrared radiometers, are usually exploited for monitoring and measuring dispersed ash clouds. The observations from geostationary orbit suffer from a relatively poor spatial resolution, whereas the low orbit level has a relatively poor temporal resolution. Moreover, the field-of-view of infrared radiometric measurements may be reduced by obstructions caused by water and ice clouds lying between the ground and the sensor's antenna. Weather radar-based observations represent an emerging technique to detect and, to a certain extent, mitigate the hazard from the ash plumes. Ground-based microwave scanning radar systems can provide the three-dimensional information about the detected ash volume with a fairly high spatial resolution every few minutes and in all weather conditions. Methodological studies have recently investigated the possibility of using single-polarization and dual-polarization ground-based radar for the remote sensing of volcanic ash cloud. In this respect, radar observations can be complementary to satellite observations. A microphysical electromagnetic characterization of volcanic ash was carried out in terms of dielectric properties, composition, size and orientation of ash particles. An extended Volcanic Ash Radar Retrieval (VARR) algorithm for single-polarization and double-polarization systems, shown in previous work, has been applied to C-band and X-band weather radar data. In this work we show radar based estimations of eruptive source parameters for Holuhraun events in the fall of 2014. This extremely gas-rich eruption was characterized by sustained lava fountaining in the first months. At the same time some ash-rich episodes were reported from the field together with minor tephra fallout occurring close to the eruption site. Since the beginning of the eruption, the Icelandic Meteorological Office (IMO) monitored the volcanic plume using two ground-based radars: a C-band weather radar (5.5 GHz) in Egilsstaðir and an X-band polarimetric mobile radar (9.4 GHz) located at Vaðalda, about 20 km away from the eruption site. The VARR algorithm has been applied to few specific events and the radar products, such as top plume height, concentration, ash load and mass flow rate, derived from the two radars, are here discussed in terms of retrievals and inter-comparisons with available in-situ information. Both radar-based estimations show a presence of volcanic particles in the observed plume. Also, airborne fine ash particles are identified at low levels of plume probably due to a wind-induced re-suspension of dust and ancient volcanic ash deposited in the area around Holuhraun.
Robertson, Franklin R.; Fitzjarrald, Dan E.; Kummerow, Christian D.; Arnold, James E. (Technical Monitor)
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.
Maccini, Sharon L.; Yang, Dean
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…
Stern, Andrew D.; Brady, Raymond H., III; Moore, Patrick D.; Carter, Gary M.
The National Weather Service Eastern Region is carrying out a national risk-reduction exercise at the Baltimore-Washington Forecast Office in Sterling, Virginia. The primary objective of this project is to integrate information from remote sensor technologies to produce comprehensive state-of-the-atmosphere reports that promote aviation safety. Techniques have been developed and tested to identify aviation-oriented hazardous weather based on data from conventional radars, a national lightning detection network, and collateral observations from new Automated Surface Observing System (ASOS) sites that are being deployed throughout the nation. From July through September 1993, an experimental observational product to identify convective activity within 30 n mi of six airports from southern Virginia to Delaware was transmitted three times each hour to personnel at Weather Service Offices and Center Weather Service Units and to the meteorologists and flight dispatchers of five major air carriers. This user-oriented evaluation and the associated statistical analysis has provided important feedback to assess the utility of the product as a supplement to ASOS. Integration of information from several products generated by the new Doppler radar at Sterling with lightning network data is being pursued for the second phase of the project. The National Weather Service will determine the viability of this approach to generate products to routinely supplement the information provided by ASOS on either a national or a local basis.
Sebastian, A.; Bedient, P.
Low slopes and shallow, impermeable soils are characteristic of the Upper Texas Gulf Coast. These, coupled with large rainfall events, contribute to wide floodplains and ponding. Rapid, high intensity development has further exacerbated flooding in this coastal region. The Clear Creek Watershed is located in southeast Houston and empties into Galveston Bay. During the past decade, the watershed has been impacted by significant historical coastal storms and rainfall events such as Tropical Storm Allison (2001), Hurricane Ike (2008), and the April 2009 Event. In this study, we employ a calibrated, distributed hydrologic model and pre- and LID-development models to analyze how development characteristics have contributed to costly flooding in coastal watersheds. In 2012, Brody et al. used FEMA floodclaims collected over the 11-year period between 1999 and 2009 to examine the pattern of flood loss across the Clear Creek watershed. The results showed that the 100-year floodplain did not adequately represent overall or event-specific loss. Using a spatial cluster analysis, the Turkey Creek sub-area of the Clear Creek watershed was pin-pointed as an area of statistically significant flood loss, an area where there were a considerable number of high-value flood claims. This area is characterized by high-density, poorly constructed development and frequent flooding. In parallel with Brody's study of flood-risk indicators, our study aims to examine the behavior of the flood-wave in the coastal watershed and how it is affected by different development patterns. A distributed hydrologic VfloTM model was built for Turkey Creek using 2008 CCAP land cover data and calibrated using NEXRAD radar rainfall for the Hurricane Ike (2008) and April 2009 events. Once the model was calibrated, both pre- and LID-development models were built using historical land cover data. These models were used to identify how development patterns have influence the flood hydrograph. Early results indicate that the construction of impervious surfaces has greatly increased the flood peak and shortened the time to peak of the flood wave. The study will go further to identify the measures that may be taken to reduce flooding in the Clear Creek Watershed and attempt to extrapolate the best management practices for low impact development in coastal watersheds.
Huang, Yulin; Zha, Yuebo; Wang, Yue; Yang, Jianyu
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
Huang, Yulin; Zha, Yuebo; Wang, Yue; Yang, Jianyu
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
Steiger, Scott Michael
-1 THUNDERSTORM LIGHTNING AND RADAR CHARACTERISTICS: INSIGHTS ON ELECTRIFICATION AND SEVERE WEATHER FORECASTING A Dissertation by SCOTT MICHAEL STEIGER Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment... Dissertation by SCOTT MICHAEL STEIGER Submitted to the Office of Graduate Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Approved by: Chair of Committee, Richard E...
Lagha, Mohand; Bergheul, Said; Rezoug, Tahar; Bettayeb, Maamar
In the civilian aviation field, the radar detection of hazardous weather phenomena (winds) is very important. This detection will allow the avoidance of these phenomena and consequently will enhance the safety of flights. In this work, we have used the wavelets method to estimate the mean velocity of winds. The results showed that the application of this method is promising compared with the classical estimators (pulse-pair, Fourier).
Jylha, Kirsti Tellervo
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.
An evaluation of the version 5 precipitation radar (PR, algorithm 2A25) and TRMM microwave imager (TMI, and (2) by comparing the rainfall from the PR and TMI on a rainfall feature- by-feature basis within is done to evaluate the overall biases of the TMI and PR to "ground truth" to examine regional differences
Collett Jr., Jeffrey L.
KDP. Theoretical modeling with experimental raindrop size distributions indicates that due to some non-weighted drop diameter, Dm, exceeds about 2 mm. Simultaneous X- and S-band radar measurements of rainfall showed data taken in light-to-moderate stratiform rainfalls with rain rates R in an interval from 2.5 to 15 mm
Koffi, A. K.; Gosset, M.; Zahiri, E.-P.; Ochou, A. D.; Kacou, M.; Cazenave, F.; Assamoi, P.
As part of the African Monsoon Multidisciplinary Analysis (AMMA) field campaign an X-band dual-polarization Doppler radar was deployed in Benin, West-Africa, in 2006 and 2007, together with a reinforced rain gauge network and several optical disdrometers. Based on this data set, a comparative study of several rainfall estimators that use X-band polarimetric radar data is presented. In tropical convective systems as encountered in Benin, microwave attenuation by rain is significant and quantitative precipitation estimation (QPE) at X-band is a challenge. Here, several algorithms based on the combined use of reflectivity, differential reflectivity and differential phase shift are evaluated against rain gauges and disdrometers. Four rainfall estimators were tested on twelve rainy events: the use of attenuation corrected reflectivity only (estimator R(ZH)), the use of the specific phase shift only R(KDP), the combination of specific phase shift and differential reflectivity R(KDP,ZDR) and an estimator that uses three radar parameters R(ZH,ZDR,KDP). The coefficients of the power law relationships between rain rate and radar variables were adjusted either based on disdrometer data and simulation, or on radar-gauges observations. The three polarimetric based algorithms with coefficients predetermined on observations outperform the R(ZH) estimator for rain rates above 10 mm/h which explain most of the rainfall in the studied region. For the highest rain rates (above 30 mm/h) R(KDP) shows even better scores, and given its performances and its simplicity of implementation, is recommended. The radar based retrieval of two parameters of the rain drop size distribution, the normalized intercept parameter NW and the volumetric median diameter Dm was evaluated on four rainy days thanks to disdrometers. The frequency distributions of the two parameters retrieved by the radar are very close to those observed with the disdrometer. NW retrieval based on a combination of ZH-KDP-ZDR works well whatever the a priori assumption made on the drop shapes. Dm retrieval based on ZDR alone performs well, but if satisfactory ZDR measurements are not available, the combination ZH-KDP provides satisfactory results for both Dm and NW if an appropriate a priori assumption on drop shape is made.
Smith, P. J.; Beven, K.; Panziera, L.
The issuing of timely flood alerts may be dependant upon the ability to predict future values of water level or discharge at locations where observations are available. Catchments at risk of flash flooding often have a rapid natural response time, typically less then the forecast lead time desired for issuing alerts. This work focuses on the provision of short-range (up to 6 hours lead time) predictions of discharge in small catchments based on utilising radar forecasts to drive a hydrological model. An example analysis based upon the Verzasca catchment (Ticino, Switzerland) is presented. Parsimonious time series models with a mechanistic interpretation (so called Data-Based Mechanistic model) have been shown to provide reliable accurate forecasts in many hydrological situations. In this study such a model is developed to predict the discharge at an observed location from observed precipitation data. The model is shown to capture the snow melt response at this site. Observed discharge data is assimilated to improve the forecasts, of up to two hours lead time, that can be generated from observed precipitation. To generate forecasts with greater lead time ensemble precipitation forecasts are utilised. In this study the Nowcasting ORographic precipitation in the Alps (NORA) product outlined in more detail elsewhere (Panziera et al. Q. J. R. Meteorol. Soc. 2011; DOI:10.1002/qj.878) is utilised. NORA precipitation forecasts are derived from historical analogues based on the radar field and upper atmospheric conditions. As such, they avoid the need to explicitly model the evolution of the rainfall field through for example Lagrangian diffusion. The uncertainty in the forecasts is represented by characterisation of the joint distribution of the observed discharge, the discharge forecast using the (in operational conditions unknown) future observed precipitation and that forecast utilising the NORA ensembles. Constructing the joint distribution in this way allows the full historic record of data at the site to inform the predictive distribution. It is shown that, in part due to the limited availability of forecasts, the uncertainty in the relationship between the NORA based forecasts and other variates dominated the resulting predictive uncertainty.
Foresti, L.; Seed, A.
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.
Gyasi-Agyei, Yeboah; Pegram, Geoffrey
Given a record of daily rainfall over a network of gauges, this paper describes a method of linking the Gauge Wetness Ratio (GWR) on a given day to the joint distribution of the parameters of the anisotropic correlogram defining the spatial statistics of simulated radar-rainfall fields. We generate a large number of Gaussian random fields by sampling from the correlogram parameters conditioned on the GWR and then conditionally merge these fields to the gauge observations transformed into the Gaussian domain. Availability of such a tool allows better spatially distributed hydrological modelling, because good quality ensemble spatial information is required for such work, as it yields uncertainty of the fields so generated. To achieve these ends, correlograms of many Gaussianised daily accumulations of radar images were developed using the Fast Fourier Transform to generate their sample power spectra. Empirical correlograms were fitted using a 2D exponential distribution to yield the 3 key parameters of the correlogram: the range, the anisotropy ratio and the direction of the major axis. It was found that the range follows a Gamma distribution while the anisotropy parameters follow a Loglogistic one; a t5 copula was adequate to capture the bivariate negative dependence structure between the range and ratio. The Radar Wetted Area Ratio (RWAR) drives the parameters of the correlogram, and its link with GWR is modelled by a transition probability matrix. We take each of the generated Gaussian random fields and conditionally merge it with Gaussianised rainfall values at the gauge locations using Ordinary Kriging. The method produces realistic simulated radar images, on a grid chosen to suit the data, which match the gauge observations at their locations. Ensemble simulations of 1000 samples were used to derive the median and the inter-quartile range of the fields; these were found to narrow near the control gauge locations, as expected, emphasising the value of high density gauge networks. Ongoing research is looking towards integration of the presented methodology with a stochastic daily rainfall generator for useful spatial rainfall simulation over catchments with gauged records.
Lee, Jean T.
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.
Walter Collischonn; Reinaldo Haas; Ivanilto Andreolli; Carlos Eduardo Morelli Tucci
The use of quantitative rainfall forecasts as input to a rainfall-runoff model, thereby extending the lead-time of flow forecasts, is relatively new. This paper presents results from a study in which real-time river flow forecasts were calculated for the River Uruguay basin lying within southern Brazil, using a method based on observed rainfall, quantitative forecasts of rainfall given by a
Virginie Marécal; Jean-François Mahfouf; Peter Bauer
The objectives of this paper are to perform a comparison between three rainfall-rate estimates from Tropical Rainfall Measuring Mission Microwave Imager (TMI) data and to study their impact in the European Centre for Medium-Range Weather Forecasts (ECMWF) four-dimensional variational (4D-Var) assimilation system. The three algorithms for rainfall estimation considered are: Precipitation Radar Adjusted TMI Estimation of Rainfall (PATER), Bayesian Algorithm
Scholl, M. A.; Coplen, T. B.
Observed patterns of isotopic composition of rainfall in the tropics are different than those at higher latitudes, where seasonal temperature changes have a large effect. Land surface temperatures vary little over the course of the year in the tropics, and the amount effect (involving evaporative enrichment, droplet size, and rainout processes) has been invoked as an explanation for variations in isotopic composition of rain measured at the land surface. Previous work by Scholl et al. (2009) in Eastern Puerto Rico showed that variations in the altitude (and temperature) of the clouds producing rain were highly correlated with the monthly stable isotope composition of rainfall. The altitude of rain droplets within the clouds was obtained using NEXRAD echo tops, which indicate the maximum altitude of rainfall determined by radar. Atmospheric temperature in rainfall-producing clouds was then estimated with archived NCEP data at the mean and maximum echo top altitudes for large rain events during the sampling period. Isotopic signatures associated with the major climate patterns in Puerto Rico were determined and are being utilized in local hydrological studies. For Eastern Puerto Rico, at latitude 18° N, ?18O and ?2H values and mean monthly echo top altitude were significantly correlated (average coefficient = -0.69). The analysis was repeated using a 24-month stable isotope data set of rain from sites on windward and leeward Maui, Hawaii, latitude 21° N. Results were similar; mean monthly echo top altitude was highly correlated with rainfall isotopic composition (windward site correlation coefficient = -0.86, leeward = -0.87). The data also showed a significant rainout effect in monthly samples dominated by tropical storms, where cloud heights were similar to other monthly samples but ?18O and ?2H values were much more negative. Variations in water vapor isotopic composition also affect isotopic composition of rain, and ongoing work will focus on investigating those factors further. Echo tops are a measurable parameter that reflects temperature, and to some extent, size and intensity of individual rain events. These results show that echo tops may be a good predictor for the isotopic composition of tropical rainfall where radar data are available, and that seasonal variations in cloud height can be factored into models to predict the isotopic composition of rain. High resolution (15-minute) rainfall samples for isotopic analysis were recently collected from outer rain bands of Hurricane Earl, which affected Puerto Rico August 30-31, 2010, and we hope to obtain more data during the remaining hurricane season. These data should yield information on within-storm variations in cloud echo tops and isotopic composition.
Krebsbach, K.; Friederichs, P.
The generation of reliable precipitation products that explicitly account for spatial and temporal structures of precipitation events requires a combination of data with a variety of error structures and temporal resolutions. In-situ measurements are relatively accurate, but available only at sparse and irregularly distributed locations, whereas remote measurements cover areas but suffer from spatially and temporally inhomogeneous systematic errors. Besides gauge measurements are available on coarser spatial and temporal resolution in contrast to remote sensing measurements which are given on a fine spatial and temporal resolution. In our study we use precipitation rates from the composit of two X-band radars in Bonn and Jülich in Germany. Our aim is to formulate a statistical space-time model that aggregates and disaggregates precipitation rates from radar and gauge observations. We model a Gaussian random field as underlying process, where we face the task of dealing with a large non-Gaussian data set. To start the analysis of the unadjusted radar rainfall rates, we follow the work of D. Allcroft and C. Glasbey (2003) and transform the data to a truncated Gaussian distribution. The advantage of the latent variable approach is that it takes account of the occurence of rainfall and the intensity using a single process. We proceed by estimating the empirical correlation from these transformed values with maximum likelihood methods and fit a parametric correlation function that gives rise to a Gaussian random field. Since the transformation gives censored values to dry locations, we simulate values for this area that lie below some threshold and extend the Gaussian field to the whole domain. In order to merge gauge and radar data for precipitation, we first aggregate the data to a scale on which the comparison is reasonable and then disaggregate again back to smaller desirable scales. The disaggregation step consists of calculating the difference between radar aggregate and small scale measurements and the difference between gauge aggregate and derived small scale measurements. Then the spatial structure of the radar anomalies is used to simulate the gauge anomalies on the whole field. In the end we add the simulation to a combined estimator of the radar and gauge aggregates and obtain the small scale merging product.
Baxa, Ernest G., Jr.; Lee, Jonggil
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.
Nickum, J. D.; Mccall, D. L.
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.
Rigo, T.; Llasat, M. C.
During the period 1996-2000, forty-three heavy rainfall events have been detected in the Internal Basins of Catalonia (Northeastern of Spain). Most of these events caused floods and serious damage. This high number leads to the need for a methodology to classify them, on the basis of their surface rainfall distribution, their internal organization and their physical features. The aim of this paper is to show a methodology to analyze systematically the convective structures responsible of those heavy rainfall events on the basis of the information supplied by the meteorological radar. The proposed methodology is as follows. Firstly, the rainfall intensity and the surface rainfall pattern are analyzed on the basis of the raingauge data. Secondly, the convective structures at the lowest level are identified and characterized by using a 2-D algorithm, and the convective cells are identified by using a 3-D procedure that looks for the reflectivity cores in every radar volume. Thirdly, the convective cells (3-D) are associated with the 2-D structures (convective rainfall areas). This methodology has been applied to the 43 heavy rainfall events using the meteorological radar located near Barcelona and the SAIH automatic raingauge network.
Brauer, Claudia; Overeem, Aart; Uijlenhoet, Remko
Several rainfall measurement techniques are available for hydrological applications, each with its own spatial and temporal resolution. We investigated the effect of differences in rainfall estimates on discharge simulations in a lowland catchment by forcing a novel rainfall-runoff model (WALRUS) with rainfall data from gauges, radars and microwave links. The hydrological model used for this analysis is the recently developed Wageningen Lowland Runoff Simulator (WALRUS). WALRUS is a rainfall-runoff model accounting for hydrological processes relevant to areas with shallow groundwater (e.g. groundwater-surface water feedback). Here, we used WALRUS for case studies in the Hupsel Brook catchment. We used two automatic rain gauges with hourly resolution, located inside the catchment (the base run) and 30 km northeast. Operational (real-time) and climatological (gauge-adjusted) C-band radar products and country-wide rainfall maps derived from microwave link data from a cellular telecommunication network were also used. Discharges simulated with these different inputs were compared to observations. Traditionally, the precipitation research community places emphasis on quantifying spatial errors and uncertainty, but for hydrological applications, temporal errors and uncertainty should be quantified as well. Its memory makes the hydrologic system sensitive to missed or badly timed rainfall events, but also emphasizes the effect of a bias in rainfall estimates. Systematic underestimation of rainfall by the uncorrected operational radar product leads to very dry model states and an increasing underestimation of discharge. Using the rain gauge 30 km northeast of the catchment yields good results for climatological studies, but not for forecasting individual floods. Simulating discharge using the maps derived from microwave link data and the gauge-adjusted radar product yields good results for both events and climatological studies. This indicates that these products can be used in catchments without gauges in or near the catchment. Uncertainty in rainfall forcing is a major source of uncertainty in discharge predictions, both with lumped and with distributed models. For lumped rainfall-runoff models, the main source of input uncertainty is associated with the way in which (effective) catchment-average rainfall is estimated. Improving rainfall measurements can improve the performance of rainfall-runoff models, indicating their potential for reducing flood damage through real-time control.
M. Yeary; R. Palmer; M. Xue; T.-Y. Yu; G. Zhang; A. Zahrai; J. Crain; Y. Zhang; R. Doviak; Q. Xu; P. Chilson
This paper describes the beginning states of a new project that will digitize radar signals coming from eight channels on the phased array antenna at the National Weather Radar Testbed (NWRT) in Norman, Oklahoma. At the current time, a single-channel digital receiver is operational to mimic the current WSR-88D capability. The multi-channel digital data will foster a new gener- ation
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.
Hildebrand, P.H. . Remote Sensing Facility)
A technique is presented for estimation of sea-surface winds using backscatter cross-section measurements from an airborne research weather radar. The technique is based on an empirical relation developed for use with satellite-borne microwave scatterometers which derives sea-surface winds from radar backscatter cross-section measurements. Unlike a scatterometer, the airborne research weather radar is a Doppler radar designed to measure atmospheric storm structure and kinematics. Designed to scan the atmosphere, the radar also scans the ocean surface over a wide range of azimuths, with the incidence angle and polarization angle changing continuously during each scan. The new sea-surface wind estimation technique accounts for these variations in incidence angle and polarization and derives the atmospheric surface winds. The technique works well over the range of wind conditions over which the wind speed-backscatter cross-section relation holds, about 2--20 m/s. The problems likely to be encountered with this new technique are evaluated and it is concluded that most problems are those which are endemic to any microwave scatterometer wind estimation technique. The new technique will enable using the research weather radar to provide measurements which would otherwise require use of a dedicated scatterometer.
Strommer, Gabriel; Brandt, Martin; Diongue-Niang, Aida; Samimi, Cyrus
In the 20th century, the West African Sahel has been a hot-spot of climatic changes. After severe drought-events in the 1970s and 1980s which were followed by a significant drop in annual precipitation, rainfall seems to increase again during the past years. Most studies are based on monthly or yearly datasets. However, many processes and events which are important for the local population depending on rainfall are not related to monthly or annual precipitation but are related to intra-annual, often daily scales. During this study, interviews with farmers and herders were conducted in the Senegalese Sahel. The results show, that wet months with unsuitably distributed precipitation can cause more harm than bringing benefits - depending on the phenological stage of the plants. Agricultural crops for example need rainfall breaks. On the other hand, natural herbaceous vegetation tolerates longer wet periods. So, a wet season can still hide dry spells that alter crops and vegetation development. Based on the results of these interviews, this study developed two indexes, one for local farmers and one for herders separately, showing if the year was favorable for them or not. The indexes integrate the length of rainy seasons, intensity and frequency of rainfall events, breaks between events and also the previous year. This way, each year is assigned to one of 5 classes. Using daily rainfall data of the Linguère weather-station (from the Senegal Meteorological Service, ANACIM), trends of the indexes from 1945 to 2002 are detected and compared to results of the interviews. Statistically relating the indexes to yearly and monthly data demonstrates, how much information can be gathered by those datasets. Furthermore, changes in intensity and frequency are related with yearly and monthly sums showing relations between daily data and annual sums. For example, a high correlation (r=0.73) between the amount of rain days (> 1 mm) and the annual rainfall is observed in Linguère.
Pavolonis, M. J.; Cintineo, J.; Sieglaff, J.; Lindsey, D. T.
The formation, maintenance, and severity of thunderstorms that produce large hail, strong winds, and tornadoes are often difficult to forecast due to their rapid evolution and complex interactions with environmental features that are challenging to directly observe. This paper describes an empirical, data driven, approach to forecasting severe convection through fusion of near real time data from several sources. More specifically, data from the Geostationary Operational Environmental Satellites (GOES), the Next Generation Weather Radar (NEXRAD) network, and the Rapid Refresh (RAP) numerical weather prediction (NWP) model are used to drive a naïve Bayesian classifier. Each observation source provides unique information during different periods of storm development (i.e., the pre-storm environment, storm initiation and growth, and hydrometeor intensification). The model is designed to provide warning guidance to forecasters in the near-term (0-60 min), by quantifying several key temporal and spatial attributes of developing convection. The probabilistic model, known as ProbSevere, has been running in near real time at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS) since April of 2013 and was formally evaluated by National Weather Service (NWS) forecasters at the Hazardous Weather Testbed (HWT) in the spring of 2014. Validation studies and forecaster feedback indicated that the ProbSevere model, which is driven by near real time data, could be used to improve severe weather warning operations. In this paper, we will give an overview of the ProbSevere model, including performance statistics, and describe how the model will benefit from the next generation of GOES satellites (GOES-R).
Wieczorek, Gerald F.; McWreath, Harry; Davenport, Clay
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.
Meneghini, Robert; Atlas, David; Fujita, Masaharu; Nakamura, Kenji
The paper describes algorithms for rain-rate profiling with an airborne or space-borne radar. Some problems involved in the radar measurements from an airborne or space-borne platform are discussed. An outline of a dual-frequency algorithm is described and its performance is confirmed by a computer simulation and an airborne experiment. A single-frequency algorithm is developed by introducing a path-integrated rain rate estimated from an attenuation of surface echoes or from microwave brightness temperature. The computer simulation shows good performance for an airborne or space-borne radar.
Kaltenboeck, Rudolf; Kerschbaum, Markus; Hennermann, Karin; Mayer, Stefan
Nowcasting of precipitation events, especially thunderstorm events or winter storms, has high impact on flight safety and efficiency for air traffic management. Future strategic planning by air traffic control will result in circumnavigation of potential hazardous areas, reduction of load around efficiency hot spots by offering alternatives, increase of handling capacity, anticipation of avoidance manoeuvres and increase of awareness before dangerous areas are entered by aircraft. To facilitate this rapid update forecasts of location, intensity, size, movement and development of local storms are necessary. Weather radar data deliver precipitation analysis of high temporal and spatial resolution close to real time by using clever scanning strategies. These data are the basis to generate rapid update forecasts in a time frame up to 2 hours and more for applications in aviation meteorological service provision, such as optimizing safety and economic impact in the context of sub-scale phenomena. On the basis of tracking radar echoes by correlation the movement vectors of successive weather radar images are calculated. For every new successive radar image a set of ensemble precipitation fields is collected by using different parameter sets like pattern match size, different time steps, filter methods and an implementation of history of tracking vectors and plausibility checks. This method considers the uncertainty in rain field displacement and different scales in time and space. By validating manually a set of case studies, the best verification method and skill score is defined and implemented into an online-verification scheme which calculates the optimized forecasts for different time steps and different areas by using different extrapolation ensemble members. To get information about the quality and reliability of the extrapolation process additional information of data quality (e.g. shielding in Alpine areas) is extrapolated and combined with an extrapolation-quality-index. Subsequently the probability and quality information of the forecast ensemble is available and flexible blending to numerical prediction model for each subarea is possible. Simultaneously with automatic processing the ensemble nowcasting product is visualized in a new innovative way which combines the intensity, probability and quality information for different subareas in one forecast image.
Reynolds, Amber Elizabeth
(KTLX) and Tulsa, Oklahoma (KINX) Weather Surveillance Radar – 1988 Doppler (WSR-88D) were used to examine the genesis of a long-lived MCV from 0000 to 0300 UTC on 11 June 2003. Traditional dual-Doppler techniques were used to determine the 3-D wind...
Chilson, P. B.; Yeary, M. B.
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…
Weather Radar and Hydrology (Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ-distributed urban hydrological model. Both probability distributions of the extremes are shown to follow a power; urban hydrology; power law INTRODUCTION This paper implements multifractal techniques (see Lovejoy
Weather Radar and Hydrology (Proceedings of a symposium held in Exeter, UK, April 2011) (IAHS Publ, and therefore classical operational notions. To take into account this aspect, the hydrological systems hydrology and it also corresponds to the lesser known scale range for precipitation fields. There are many
Sieges, Mason L.; Smolinsky, Jaclyn A.; Baldwin, Michael J.; Barrow, Wylie C.; Randall, Lori A.; Buler, Jeffrey J.
In response to the Deepwater Horizon oil spill in spring 2010, the Natural Resources Conservation Service implemented the Migratory Bird Habitat Initiative (MBHI) to provide temporary wetland habitat for migrating and wintering waterfowl, shorebirds, and other birds along the northern Gulf of Mexico via managed flooding of agricultural lands. We used weather-surveillance radar to conduct broad regional assessments of bird response to MBHI activities within the Mississippi Alluvial Valley and the West Gulf Coastal Plain. Across both regions, birds responded positively to MBHI management by exhibiting greater relative bird densities within sites relative to pre-management conditions in prior years and relative to surrounding non-flooded agricultural lands. Bird density at MBHI sites was generally greatest during winter for both regions. Unusually high flooding in the years prior to implementation of the MBHI confounded detection of overall changes in remotely sensed soil wetness across sites. The magnitude of bird response at MBHI sites compared to prior years and to non-flooded agricultural lands was generally related to the surrounding landscape context: proximity to areas of high bird density, amount of forested wetlands, emergent marsh, non-flooded agriculture, or permanent open water. However, these relationships varied in strength and direction between regions and seasons, a finding which we attribute to differences in seasonal bird composition and broad regional differences in landscape configuration and composition. We detected greater increases in relative bird use at sites in closer proximity to areas of high bird density during winter in both regions. Additionally, bird density was greater during winter at sites with more emergent marsh in the surrounding landscape. Thus, bird use of managed wetlands could be maximized by enrolling lands located near areas of known bird concentration and within a mosaic of existing wetlands. Weather-radar observations provide strong evidence that MBHI sites located inland from coastal wetlands impacted by the oil spill provided wetland habitat used by a variety of birds.
Tropical rainfall affects the lives and economics of a majority of the Earth's population. Tropical rain systems, such as hurricanes, typhoons, and monsoons, are crucial to sustaining the livelihoods of those living in the tropics. Excess rainfall can cause floods and great property and crop damage, whereas too little rainfall can cause drought and crop failure. The latent heat release during the process of precipitation is a major source of energy that drives the atmospheric circulation. This latent heat can intensify weather systems, affecting weather thousands of kilometers away, thus making tropical rainfall an important indicator of atmospheric circulation and short-term climate change. Tropical forests and the underlying soils are major sources of many of the atmosphere's trace constituents. Together, the forests and the atmosphere act as a water-energy regulating system. Most of the rainfall is returned to the atmosphere through evaporation and transpiration, and the atmospheric trace constituents take part in the recycling process. Hence, the hydrological cycle provides a direct link between tropical rainfall and the global cycles of carbon, nitrogen, and sulfur, all important trace materials for the Earth's system. Because rainfall is such an important component in the interactions between the ocean, atmosphere, land, and the biosphere, accurate measurements of rainfall are crucial to understanding the workings of the Earth-atmosphere system. The large spatial and temporal variability of rainfall systems, however, poses a major challenge to estimating global rainfall. So far, there has been a lack of rain gauge networks, especially over the oceans, which points to satellite measurement as the only means by which global observation of rainfall can be made. The Tropical Rainfall Measuring Mission (TRMM), jointly sponsored by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan, provides visible, infrared, and microwave observations of tropical and subtropical rain systems.The satellite observations are complemented by ground radar and rain gauge measurements to validate satellite rain estimation techniques. Goddard Space Flight Center's involvement includes the observatory, four instruments, integration and testing of the observatory, data processing and distribution, and satellite operations. TRMM has a design lifetime of three years. Data generated from TRMM and archived at the GDAAC are useful not only for hydrologists, atmospheric scientists, and climatologists, but also for the health community studying infectious diseases, the ocean research community, and the agricultural community.
Prat, O. P.; Barros, A. P.
A Micro Rain Radar (MRR) was deployed twice in July/August and October/November 2008 for a total duration of three months at the top of a mountain ridge in the Great Smoky Mountains National Park in the Southern Appalachians. For the second period of observation, a second MRR was deployed at a lower altitude in a nearby valley. Observations from rain gauges and the MRR were used along with a microphysical model to simulate the rainfall events observed during the radar deployment. Results from an integrated analysis of the observations are presented here, with emphasis on characterizing the diurnal cycle of rainfall and ridge-valley gradients in vertical structure of rainfall with an emphasis on microphysical properties.
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
Fiolleau, T.; Roca, R.; Angelis, F. C.; Viltard, N.
In the tropics most of the rainfall comes in the form of individual storm events embedded in the synoptic circulations (e.g., monsoons). Understanding the rainfall and its variability hence requires to document these highly contributing tropical convective systems (MCS). Our knowledge of the MCS life cycle, from a physical point of view mainly arises from individual observational campaigns heavily based on ground radar observations. While this large part of observations enabled the creation of conceptual models of MCS life cycle, it nevertheless does not reach any statistically significant integrated perspective yet. To overcome this limitation, a composite technique, that will serve as a Day-1 algorithm for the Megha-Tropiques mission, is considered in this study. this method is based on a collocation in space and time of the level-2 rainfall estimates (BRAIN) derived from the TMI radiometer onboard TRMM with the cloud systems identified by a new MCS tracking algorithm called TOOCAN and based on a 3-dimensional segmentation (image + time) of the geostationary IR imagery. To complete this study, a similar method is also developed collocating the cloud systems with the precipitating features derived from the ground weather radar which has been deployed during the CHUVA campaign over several Brazilian regions from 2010 up to now. A comparison of the MCSs life cycle is then performed for the 2010-2012 summer seasons over the West African, and South American regions. On the whole region of study, the results show that the temporal evolution of the cold cloud shield associated to MCSs describes a symmetry between the growth and the decay phases. It is also shown that the parameters of the conceptual model of MCSs are strongly correlated, reducing thereby the problem to a single degree of freedom. At the system scale, over both land and oceanic regions, rainfall is described by an increase at the beginning (the first third) of the life cycle and then smoothly decreases as the system shrinks and dissipates. The evolutions of the precipitating properties associated to MCSs indicate that the life cycle of these systems can be described by three phases: initiation, mature and dissipation. This pattern is robust across the entire monsoonal region and the scale factors of this idealized model indicate complex regional specificities.
Reading, University of
drop size (Seliga and Bringi 1976) and hence can be used to refine rain-rate esti- mates. Differential alone, not only by better characterization of the drop size distribution, but also by more reliable in the size distribution. Conven- tional radars are also unable to distinguish hail from heavy rain
Seo, B.; Dolan, B.; Krajewski, W. F.; Rutledge, S. A.; Petersen, W. A.
During the months of April to June 2013, NASA conducted a field experiment called Iowa Flood Studies (IFloodS) as part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission in the central and northeastern Iowa in the United States. The purpose of IFloodS is to enhance the understanding of flood-related precipitation processes in events worldwide. While there are multiple rainfall data sets (satellite, radar, and ground reference data products) available as legacy from IFloodS, the authors focus on the comparison of the NEXRAD single and dual polarization precipitation products to evaluate potential benefits of using dual polarization data for flood-related precipitation events. The Hydro-NEXRAD and CSU (Colorado State University)-HIDRO blended precipitation processing algorithms were used to generate single and dual polarization products, respectively. Data from four NEXRAD radars (Des Moines, IA; Davenport, IA; Minneapolis, MN; and La Crosse, WI) were combined to cover the study area. Uncertainties of both products using dense networks of ground reference (e.g., rain gauge and disdrometer) are characterized. Major differences and similarities based on the observed precipitation cases are also discussed.
Plaut, Jeffrey J.; Rivard, Benoit
Radar backscatter intensity as measured by calibrated synthetic aperture radar (SAR) systems is primarily controlled by three factors: local incidence angle, wavelength-scale roughness, and dielectric permittivity of surface materials. Radar observations may be of limited use for geological investigations of surface composition, unless the relationships between lithology and the above characteristics can be adequately understood. In arid terrains, such as the Southwest U.S., weathering signatures (e.g. soil development, fracturing, debris grain size and shape, and hill slope characteristics) are controlled to some extent by lithologic characteristics of the parent bedrock. These textural features of outcrops and their associated debris will affect radar backscatter to varying degrees, and the multiple-wavelength capability of the JPL Airborne SAR (AIRSAR) system allows sampling of textures at three distinct scales. Diurnal temperature excursions of geologic surfaces are controlled primarily by the thermal inertia of surface materials, which is a measure of the resistance of a material to a change in temperature. Other influences include albedo, surface slopes affecting insolation, local meteorological conditions and surface emissivity at the relevant thermal wavelengths. To first order, thermal inertia variations on arid terrain surfaces result from grain size distribution and porosity differences, at scales ranging from micrometers to tens of meters. Diurnal thermal emission observations, such as those made by the JPL Thermal Infrared Multispectral Scanner (TIMS) airborne instrument, are thus influenced by geometric surface characteristics at scales comparable to those controlling radar backscatter. A preliminary report on a project involving a combination of field, laboratory and remote sensing observations of weathered felsic-to basaltic volcanic rock units exposed in the southern part of the Lunar Crater Volcanic Field, in the Pancake Range of central Nevada is presented. Focus is on the relationship of radar backscatter cross sections at multiple wavelengths, apparent diurnal temperature excursions identified in multi-temporal TIMS images, surface geometries related to weathering style, and parent bedrock lithology.
Hadley, Jennifer Lynn
-time flood warning system application. Ogden et al. (2000) used NEXRAD rainfall data with the CASC2D model to evaluate hydrologic prediction of extreme events in urban environments in the Spring Creek watershed in Fort Collins, Colorado. They found................................................... 16 4.2.2. Red River Basin..................................................... 19 4.2.3. Lower Colorado River Basin................................. 21 4.2.4. San Antonio River Basin....................................... 22 4.3. Estimating...
Sharif, H. O.; Chintalapudi, S.; El Hassan, A.
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.
Luitel, B. N.; Villarini, G.; Vecchi, G. A.
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.
Wang, Minzhong; Wei, Wenshou; Ruan, Zheng; He, Qing; Ge, Runsheng
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
This lesson is written for fourth grade students. Students will explore weather and the effects it has on their lives. What is weather? video of what is weather Let's take a walk through the weather. Put on your hats and coats! Clouds Cloud Types Clouds - Dan's Wild Weather Page What to Wear? What to Wear? What to Drink? Weather Patterns and Climatic Regions ...
Have you ever wondered how the weather man, or meteorolgist, on TV knows what to say about tomorrow\\'s weather? It\\'s because they have certain tools that they use that help them predict what the weather will be. Throughout this school year you are going to be making tools and predicting weather just like a meterorologist! Task You are going to be weather forcasters! You are going to record and track weather patterns throughout the year. You will also use weather tools to make predictions about the weather like real weather forecasters! The Process 1. First we need to learn a little bit about weather so ...
Pistotnik, G.; Klebinder, K.; Chifflard, P.; Kirnbauer, R.; Haiden, T.
Torrent hazards in mountain areas in the eastern part of Lower Austria are mostly triggered by convective rainfall events during thunderstorms. The Austrian Avalanche and Torrent Control Service commissioned a project for a regional analysis of torrent hazard potential in the region Bucklige Welt / Wechselland as the basis for detailed investigations and torrent control measures which will be planned later, taking into account the hazard potential of individual streams, the most dangerous first, the less dangerous later. Thus, the following problems had to be analysed: Are there any typical points of origin of convective storms in or near the project region? Are there any typical tracks of these storms endangering the region, and what is their extent and lifetime? Which catchments generate more and which less runoff caused by the same precipitation amount? For approaching the meteorological part of the integrated problem the precipitation is estimated from radar data on a 15 minutes basis with a spatial resolution of 1 km, because no sufficient precipitation measurements are available. Within the nowcasting system INCA (Integrated Nowcasting through Comprehensive Analysis) of the Central Institute for Meteorology and Geodynamics (ZAMG) these radar data are combined with satellite data, ground data, model data from the meteorological local area model "ALADIN Vienna" and with a digital terrain model of 1 km grid space. Thus, a continuous set of precipitation fields were calculated for the years 2003 to 2007 with a temporal resolution of 15 minutes and a local resolution of 1 km. Based on this data set convective cells were identified and their tracks analysed. If a precipitation intensity of 3,8 mm/15 min was exceeded, in accordance with experiences of the meteorological remote sensing group of the ZAMG, it was a-priori assumed that this was a convective storm. According to this threshold nearly 350 convective events were automatically extracted. After discarding approximately about one third of these events as spurious the tracks of the remaining 245 cells were identified. The locations of the origin of these cells were in accordance with the experience of synoptic meteorologists, and the tracks, as to their motion direction averaged over the whole observation period of five years, followed the main wind direction in the region. Within the day of the event and from one to the next time step of 15 minutes, however, the motion of the cells was rather erratic, and their motion vectors could be described by normal distributions for speed and angle. As to their shape, the cells can be approximated by circles of changing radius: first small, then growing to a maximum size and then shrinking. The maximum diameter can be approximated by a two parameter log normal distribution, and such is the lifetime of the cells and the rainfall intensity. Due to the short observation period the intensities cannot be directly used for design purposes but have to be extrapolated to the design intensities supplied by the Hydrological Service. Intensive field studies were performed for assessing the runoff behaviour of the catchments. On nine locations irrigation experiments took place by use of a transportable spray irrigation installation with rain intensities of approximately 100mm/h on plots of 80m² and they were accompanied by soil moisture measurements with TDR probes. They were situated in two profiles of the irrigation plots and in 5, 15, 25 and 40 cm depth respectively. Six undisturbed soil cores were taken with cylindrical samplers (200 cm³ volume each) in four depths down to 50 cm. The samples were analysed with respect to their soil type, soil texture, bulk density, porosity and saturated conductivity. Thus, the results of the irrigation experiments could be thoroughly interpreted with the additional information on soil moisture dynamics and physical characteristics. For the irrigation plots and for additional 350 locations standardized investigations referring to vegetation, surface roughness, upper soil layers, deep soil
on the island of Bornholm in the Baltic Sea. Geographical location of the radar sites is illustrated in fig. 1 at Stevns suffers from sea clutter as the radar is unfortunately situated only ~ 100 m from coast on a ~ 40
Kumagai, Hiroshi; Meneghini, Robert; Kozu, Toshiaki
The study presents preliminary results from an airborne radar/radiometer experiment (Typhoon Experiment) which was conducted in the western Pacific Ocean during September 1990, with emphasis on the multiparameter radar results. One of the objectives of this experiment is to make radar/radiometer measurements over rain to support the algorithm development and science studies for the Tropical Rainfall Measuring Mission (TRMM) and the spaceborne weather sensors. The extremely high linear depolarization ratio value observed at the melting height is considered to be procured by the melting particle with large eccentricity. It is shown that the multiparameter airborne radar provides valuable information by distinguishing the hydrometeor particles of the rainfall.
Lau, William K. M. (Technical Monitor); Bell, Thomas L.; Steiner, Matthias; Zhang, Yu; Wood, Eric F.
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.
Crouch, John F.; Pardo, Natalia; Miller, Craig A.
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.
Overeem, A.; Leijnse, H.; Uijlenhoet, R.
Accurate rainfall observations with high spatial and temporal resolutions are needed for many applications, for instance, as input for hydrological models. Weather radars often provide data with sufficient spatial and temporal resolution, but usually need adjustment. In general, only few rain gauge measurements are available to adjust the radar data in real-time, for example, each hour. Physically based methods, such as a VPR correction, can be valuable and hold a promise. However, they are not always performed in real-time yet and can be difficult to implement. The estimation of rainfall using microwave links from commercial cellular telephone networks is a new and potentially valuable source of information. Such networks cover large parts of the land surface of the earth and have a high density. The data produced by the microwave links in such networks is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A recent study of us shows that urban rainfall can be estimated from commercial microwave link data for the Rotterdam region, a densely-populated delta city in the Netherlands. A data set from a commercial microwave link network over the Netherlands is analyzed, containing approximately 1500 links covering the land surface of the Netherlands (35500 km2). This data set consists of several days with extreme rainfall in June, July and August 2011. A methodology is presented to derive rainfall intensities and daily rainfall depths from the microwave link data, which have a temporal resolution of 15 min. The magnitude and dynamics of these rainfall intensities is compared with those obtained from weather radar. Rainfall maps are derived from the microwave link data and are verified against rainfall maps based on gauge-adjusted weather radar data. Although much more work needs to be done, the first results look promising. Since cellular telephone networks are used worldwide, data from such networks could also become a valuable source of rainfall information in countries which do not have continuously operating weather radars, and no or few rain gauges. Apart from rainfall maps which are solely based on microwave link data, a preliminary analysis will be presented to assess whether commercial microwave link data can be used to adjust radar rainfall accumulations.
Furuzawa, Fumie A.; Nakamura, Kenji
It is well known that precipitation rate estimation is poor over land. Using the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI), the performance of the TMI rain estimation was investigated. Their differences over land were checked by using the orbit-by-orbit data for June 1998, December 1998, January 1999, and February 1999, and the following results were obtained: 1) Rain rate (RR) near the surface for the TMI (TMI-RR) is smaller than that for the PR (PR-RR) in winter; it is also smaller from 0900 to 1800 LT. These dependencies show some variations at various latitudes or local times. 2) When the storm height is low (<5 km), the TMI-RR is smaller than the PR-RR; when it is high (>8 km), the PR-RR is smaller. These dependencies of the RR on the storm height do not depend on local time or latitude. The tendency for a TMI-RR to be smaller when the storm height is low is more noticeable in convective rain than in stratiform rain. 3) Rain with a low storm height predominates in winter or from 0600 to 1500 LT, and convective rain occurs frequently from 1200 to 2100 LT. Result 1 can be explained by results 2 and 3. It can be concluded that the TMI underestimates rain with low storm height over land because of the weakness of the TMI algorithm, especially for convective rain. On the other hand, it is speculated that TMI overestimates rain with high storm height because of the effect of anvil rain with low brightness temperatures at high frequencies without rain near the surface, and because of the effect of evaporation or tilting, which is indicated by a PR profile and does not appear in the TMI profile. Moreover, it was found that the PR rain for the cases with no TMI rain amounted to about 10%-30% of the total but that the TMI rain for the cases with no PR rain accounted for only a few percent of the TMI rain. This result can be explained by the difficulty of detecting shallow rain with the TMI.
Versini, Pierre-Antoine; Sempere-Torres, Daniel
Important damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions. These are major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods and different kinds of rainfall observations are available in real time: radar rainfall estimates and nowcasts from METEO FRANCE and the CALAMAR system from SPC (state authority in charge of flood forecasting). An application devoted to the road network, has also been recently developed for this region. It combines distributed hydro-meteorological very short range forecasts and vulnerability analysis to provide warnings of road submersions. The first results demonstrate that it is technically possible to provide distributed short-term forecasts for a large number of sites. The study also demonstrates that a reliable estimation of the spatial distribution of rainfall is essential. For this reason, the road submersion warning system can be used to evaluate the quality of rainfall estimates and nowcasts. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, more than 300mm dropped on the South part of the Gard and many roads were submerged. Each of the mentioned rainfall datasets (i.e. estimates and nowcasts) was available in real time. They have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. The results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and a reasonable false alarm ratio. It demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall nowcasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding one hour.
Hanshaw, M. N.; Schmidt, K. M.; Jorgensen, D. P.; Stock, J. D.
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 SMART-R also recorded higher seasonal cumulative rainfall than the terrestrial gages, perhaps indicating that not all precipitation reached the ground. For one storm in particular, time-lapse photographs of the ground document snow. This could explain, in part, the discrepancy between storm-specific totals when the rain gages recorded significantly lower totals than the SMART-R. For example, during the storm where snow was observed, the SMART-R recorded a maximum of 66% higher rainfall than the maximum recorded by the gages. Unexpectedly, the highest elevation gage, located in a pre-fire coniferous vegetation community, consistently recorded the lowest precipitation, whereas gages in the lower elevation pre- fire chaparral community recorded the highest totals. The spatial locations of the maximum rainfall inferred by the SMART-R and the terrestrial gages are also offset by 1.6 km, with terrestrial values shifted easterly. The observation that the SMART-R images high rainfall intensities recorded by rain gages suggests that this technology has the ability to quantitatively estimate the spatial distribution over larger areas at a high resolution. Discrepancies on the storm scale, however, need to be investigated further, but we are optimistic that such high resolution data from the SMART-R and the terrestrial gages may lead to the effective application of a prototype debris-flow warning system where such processes put lives at risk.
avoidance capability has increased. In this thesis, an intelligent weather agent is developed for general aviation aircraft. Using a radar image from an onboard weather radar, the intelligent weather agent determines the safest path around severe weather...
Devasthale, A.; Norin, L.
Using measurements from the national network of 12 weather radar stations for the last decade (2000-2010), we investigate the large-scale spatio-temporal variability of precipitation over Sweden. These statistics provide useful information to evaluate regional climate models as well as for hydrology and energy applications. A strict quality control is applied to filter out noise and artifacts from the radar data. We focus on investigating four distinct aspects namely, the diurnal cycle of precipitation and its seasonality, the dominant time scale (diurnal vs. seasonal) of variability, precipitation response to different wind directions, and the correlation of precipitation events with the North Atlantic Oscillation (NAO) and the Arctic Oscillation (AO). When classified based on their intensity, moderate to high intensity events (precipitation > 0.34 mm (3 h)-1) peak distinctly during late afternoon over the majority of radar stations in summer and during late night or early morning in winter. Precipitation variability is highest over the southwestern parts of Sweden. It is shown that the high intensity events (precipitation > 1.7mm (3 h)-1) are positively correlated with NAO and AO (esp. over northern Sweden), while the low intensity events are negatively correlated (esp. over southeastern parts). It is further observed that southeasterly winds often lead to intense precipitation events over central and northern Sweden, while southwesterly winds contribute most to the total accumulated precipitation for all radar stations. Apart from its operational applications, the present study demonstrates the potential of the weather radar data set for studying climatic features of precipitation over Sweden.
This course handout covers the processes and effects of weathering. The purpose of this handout is to contrast weathering and erosion, contrast and discuss chemical and mechanical weathering, list the products resulting from the chemical weathering of igneous rocks, and list and discuss the factors that influence the type and rate of rock weathering. Many photographs accompany this summary which depict weathered landscapes. Links are provided to the online Physical Geology resources at Georgia Perimeter College.
Meteorologists study the weather by recording and analyzing data. You can become an amateur meteorologist by building your own weather station and keeping a record of your measurements. After a while, you\\'ll notice the weather patterns that allow meteorologists to forecast the weather. Tasks: 1. As a group you will build a weather station outside. 2. Your group will build instruments to measure the weather. 3. Each person will record the data in personal weather journals. Process: 1.Since weather happens outside, you\\'ll need to make ...
Norin, L.; Devasthale, A.; L'Ecuyer, T. S.; Wood, N. B.; Smalley, M.
To be able to estimate snowfall accurately is important for both weather and climate applications. Ground-based weather radars and space-based satellite sensors are often used as viable alternatives to rain-gauges to estimate precipitation in this context. The Cloud Profiling Radar (CPR) onboard CloudSat is especially proving to be a useful tool to map snowfall globally, in part due to its high sensitivity to light precipitation and ability to provide near-global vertical structure. The importance of having snowfall estimates from CloudSat/CPR further increases in the high latitude regions as other ground-based observations become sparse and passive satellite sensors suffer from inherent limitations. Here we intercompared snowfall estimates from two observing systems, CloudSat and Swerad, the Swedish national weather radar network. Swerad offers one of the best calibrated data sets of precipitation amount at very high latitudes that are anchored to rain-gauges and that can be exploited to evaluate usefulness of CloudSat/CPR snowfall estimates in the polar regions. In total 7.2×105 matchups of CloudSat and Swerad over Sweden were inter-compared covering all but summer months (October to May) from 2008 to 2010. The intercomparison shows encouraging agreement between these two observing systems despite their different sensitivities and user applications. The best agreement is observed when CloudSat passes close to a Swerad station (46-82 km), when the observational conditions for both systems are comparable. Larger disagreements outside this range suggest that both platforms have difficulty with shallow snow but for different reasons. The correlation between Swerad and CloudSat degrades with increasing distance from the nearest Swerad station as Swerad's sensitivity decreases as a function of distance and Swerad also tends to overshoots low level precipitating systems further away from the station, leading to underestimation of snowfall rate and occasionally missing the precipitation altogether. Further investigations of various statistical metrics, such as the probability of detection, false alarm rate, hit rate, and the Hanssen-Kuipers skill scores, and the sensitivity of these metrics to snowfall rate and the distance from the radar station, were carried out. The results of these investigations highlight the strengths and the limitations of both observing systems at the lower and upper ends of snowfall distributions and the range of uncertainties that could be expected from these systems in the high latitude regions.
Marra, Francesco; Morin, Efrat
Intensity-duration-frequency (IDF) curves are widely used in flood risk management since they provide an easy link between the characteristics of a rainfall event and the probability of its occurrence. They are estimated analyzing the extreme values of rainfall records, usually basing on raingauge data. This point-based approach raises two issues: first, hydrological design applications generally need IDF information for the entire catchment rather than a point, second, the representativeness of point measurements decreases with the distance from measure location, especially in regions characterized by steep climatological gradients. Weather radar, providing high resolution distributed rainfall estimates over wide areas, has the potential to overcome these issues. Two objections usually restrain this approach: (i) the short length of data records and (ii) the reliability of quantitative precipitation estimation (QPE) of the extremes. This work explores the potential use of weather radar estimates for the identification of IDF curves by means of a long length radar archive and a combined physical- and quantitative- adjustment of radar estimates. Shacham weather radar, located in the eastern Mediterranean area (Tel Aviv, Israel), archives data since 1990 providing rainfall estimates for 23 years over a region characterized by strong climatological gradients. Radar QPE is obtained correcting the effects of pointing errors, ground echoes, beam blockage, attenuation and vertical variations of reflectivity. Quantitative accuracy is then ensured with a range-dependent bias adjustment technique and reliability of radar QPE is assessed by comparison with gauge measurements. IDF curves are derived from the radar data using the annual extremes method and compared with gauge-based curves. Results from 14 study cases will be presented focusing on the effects of record length and QPE accuracy, exploring the potential application of radar IDF curves for ungauged locations and providing insights on the use of radar QPE for hydrological design studies.
Bluestein, H. B.; Doviak, R. J.; Eilts, M. D.; Mccaul, E. W.; Rabin, R.; Sundara-Rajan, A.; Zrnic, D. S.
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.
Shepherd, J. Marshall
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.
El-Dardiry, H. A.; Habib, E. H.
Radar-based technologies have made spatially and temporally distributed quantitative precipitation estimates (QPE) available in an operational environmental compared to the raingauges. The floods identified through flash flood monitoring and prediction systems are subject to at least three sources of uncertainties: (a) those related to rainfall estimation errors, (b) those due to streamflow prediction errors due to model structural issues, and (c) those due to errors in defining a flood event. The current study focuses on the first source of uncertainty and its effect on deriving important climatological characteristics of extreme rainfall statistics. Examples of such characteristics are rainfall amounts with certain Average Recurrence Intervals (ARI) or Annual Exceedance Probability (AEP), which are highly valuable for hydrologic and civil engineering design purposes. Gauge-based precipitation frequencies estimates (PFE) have been maturely developed and widely used over the last several decades. More recently, there has been a growing interest by the research community to explore the use of radar-based rainfall products for developing PFE and understand the associated uncertainties. This study will use radar-based multi-sensor precipitation estimates (MPE) for 11 years to derive PFE's corresponding to various return periods over a spatial domain that covers the state of Louisiana in southern USA. The PFE estimation approach used in this study is based on fitting generalized extreme value distribution to hydrologic extreme rainfall data based on annual maximum series (AMS). Some of the estimation problems that may arise from fitting GEV distributions at each radar pixel is the large variance and seriously biased quantile estimators. Hence, a regional frequency analysis approach (RFA) is applied. The RFA involves the use of data from different pixels surrounding each pixel within a defined homogenous region. In this study, region of influence approach along with the index flood technique are used in the RFA. A bootstrap technique procedure is carried out to account for the uncertainty in the distribution parameters to construct 90% confidence intervals (i.e., 5% and 95% confidence limits) on AMS-based precipitation frequency curves.
Guardiola-Albert, Carolina; River-Honegger, Carlos; Yagüe, Carlos; Agut, Robert Monjo i.; Díez-Herrero, Andrés; María Bodoque, José; José Tapiador, Francisco
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.
What are the different types of weather? In this project you will compare different types of weather by drawing pictures and making it into a flip book. First you will begin by learning about the different types of weather. Read about each topic. Then get together with your partner and draw a picture of each type of weather. 1. Thunder storm Thunder storm Thunder storm Kids 2. Lightning Lightning Lightning picture 3. Tornado Tornadoes Tornado Kids 4. ...
Javelle, Pierre; Defrance, Dimitri; Ecrepont, Stéphane; Fouchier, Catherine; Mériaux, Patrice; Tolsa, Mathieu; Westrelin, Samuel
The knowledge of precipitations still remains a tricky issue in mountaineous areas: the available rain-gauges are in a limited number and most often located in the valleys, and the radar rainfall estimates have to deal with a lot of problems due to the relief and the difficulty to distinguish the different types of hydrometeors (snow, hail, rain). In this context, the "RHYTMME" project deals with two main issues: - Providing an accurate radar rainfall information in mountainous areas. - Developing a real-time hazards warning system based on this information. To answer to the first issue, a X-band doppler dual polarized radar network is currently implemented in the French South Alps. At the end of the project (2013), three new radars will be installed, completing a pre-existing radar already installed on the Mont Vial top since 2008 (Hydrix® technology developed by the Novimet company, and tested in a previous project). The present communication focuses on the flash flood warning issue. It presents some results obtained by coupling the radar estimates to a simple distributed hydrological model (the AIGA method). Results are compared on damages observed by end-users, which were strongly involved into the project. The RHYTMME project is co-piloted by Meteo-France and the Cemagref and has the financial support of the European Union, the Provence-Alpes-Côte d'Azur Region and the French Ministry in charge of Ecology.
Luce, Hubert; Mega, Tomoaki; Yamamoto, Masayuki K.; Yamamoto, Mamoru; Hashiguchi, Hiroyuki; Fukao, Shoichiro; Nishi, Noriyuki; Tajiri, Takuya; Nakazato, Masahisa
Using the very high frequency (46.5 MHz) middle and upper atmosphere radar (MUR), Ka band (35 GHz) and X band (9.8 GHz) weather radars, a Kelvin-Helmholtz (KH) instability occurring at a cloud base and its impact on modulating cloud bottom altitudes are described by a case study on 8 October 2008 at the Shigaraki MU Observatory, Japan (34.85°N, 136.10°E). KH braids were monitored by the MUR along the slope of a cloud base gradually rising with time around an altitude of ˜5.0 km. The KH braids had a horizontal wavelength of about 3.6 km and maximum crest-to-trough amplitude of about 1.6 km. Nearly monochromatic and out of phase vertical air motion oscillations exceeding ±3 m s-1 with a period of ˜3 min 20 s were measured by the MUR above and below the cloud base. The axes of the billows were at right angles of the wind and wind shear both oriented east-north-east at their altitude. The isotropy of the radar echoes and the large variance of Doppler velocity in the KH billows (including the braids) indicate the presence of strong turbulence at the Bragg (˜3.2 m) scale. After the passage of the cloud system, the KH waves rapidly damped and the vertical scale of the KH braids progressively decreased down to about 100 m before their disappearance. The radar observations suggest that the interface between clear air and cloud was conducive to the presence of the dynamical shear instability by reducing static stability (and then the Richardson number) near the cloud base. Downward cloudy protuberances detected by the Ka band radar had vertical and horizontal scales of about 0.6-1.1 and 3.2 km, respectively, and were clearly associated with the downward air motions. Observed oscillations of the reflectivity-weighted Doppler velocity measured by the X band radar indicate that falling ice particles underwent the vertical wind motions generated by the KH instability to form the protuberances. The protuberances at the cloud base might be either KH billow clouds or perhaps some sort of mamma. Reflectivity-weighted particle fall velocity computed from Doppler velocities measured by the X band radar and the MUR showed an average value of 1.3 ms-1 within the cloud and in the protuberance environment.
Roeder, W.P.; Peterson, W.A.; Carey, L.D.; Deierling, W.; McNamara, T.M.
A new weather radar is being acquired for use in support of America s space program at Cape Canaveral Air Force Station, NASA Kennedy Space Center, and Patrick AFB on the east coast of central Florida. This new radar includes dual polarization capability, which has not been available to 45 WS previously. The 45 WS has teamed with NSSTC with funding from NASA Marshall Spaceflight Flight Center to improve their use of this new dual polarization capability when it is implemented operationally. The project goals include developing a temperature profile adaptive scan strategy, developing training materials, and developing forecast techniques and tools using dual polarization products. The temperature profile adaptive scan strategy will provide the scan angles that provide the optimal compromise between volume scan rate, vertical resolution, phenomena detection, data quality, and reduced cone-of-silence for the 45 WS mission. The mission requirements include outstanding detection of low level boundaries for thunderstorm prediction, excellent vertical resolution in the atmosphere electrification layer between 0 C and -20 C for lightning forecasting and Lightning Launch Commit Criteria evaluation, good detection of anvil clouds for Lightning Launch Commit Criteria evaluation, reduced cone-of-silence, fast volume scans, and many samples per pulse for good data quality. The training materials will emphasize the appropriate applications most important to the 45 WS mission. These include forecasting the onset and cessation of lightning, forecasting convective winds, and hopefully the inference of electrical fields in clouds. The training materials will focus on annotated radar imagery based on products available to the 45 WS. Other examples will include time sequenced radar products without annotation to simulate radar operations. This will reinforce the forecast concepts and also allow testing of the forecasters. The new dual polarization techniques and tools will focus on the appropriate applications for the 45 WS mission. These include forecasting the onset of lightning, the cessation of lightning, convective winds, and hopefully the inference of electrical fields in clouds. This presentation will report on the results achieved so far in the project.
Brochero, D.; Anctil, F.; Gagné, C.
In input selection (or feature selection), modellers are interested in identifying k of the d dimensions that provide the most information. In hydrology, this problem is particularly relevant when dealing with temporally and spatially distributed data such as radar rainfall estimates or meteorological ensemble forecasts. The most common approaches for input determination of artifitial neural networks (ANN) in water resources are cross-correlation, heuristics, embedding window analysis (chaos theory), and sensitivity analyses. We resorted here to Forward Greedy Selection (FGS), a sensitivity analysis, for identifying the inputs that maximize the performance of ANN forecasting. It consists of a pool of ANNs with different structures, initial weights, and training data subsets. The stacked ANN model was setup through the joint use of stop training and a special type of boosting for regression known as AdaBoost.RT. Several ANN are then used in series, each one exploiting, with incremental probability, data with relative estimation error higher than a pre-set threshold value. The global estimate is then obtained from the aggregation of the estimates of the models (here the median value). Two schemes are compared here, which differ in their input type. The first scheme looks at lagged radar rainfall estimates averaged over entire catchment (the average scenario), while the second scheme deals with the spatial variation fields of the radar rainfall estimates (the distributed scenario). Results lead to three major findings. First, stacked ANN response outperforms the best single ANN (in the same way as many others reports). Second, a positive gain in the test subset of around 20%, when compared to the average scenario, is observed in the distributed scenario. However, the most important result from the selecting process is the final structure of the inputs, for the distributed scenario clearly outlines the areas with the greatest impact on forecasting in terms of the estimated radar precipitation and the forecast horizon. Thus, this research facilitates interpretability of the results under a downward approach, in which the zones of influence of rainfall at different forecasting horizons help understanding the pattern of the hydrologic response at the event scale. Third, the input selection is slightly different between experiments due to the active principle of diversity, defined as hydrological model complementarities addressing different aspects of the forecast. Finally the following guidelines favoured efficient stacked ANNs: i) design different combiners, ii) base the stack preprocess on probabilistic score representations oriented toward the bias of the ensemble (e.g. the ignorance score), and iii) evaluate more powerful multi-criterion selection algorithms such as multiobjective evolutionary algorithms (MOEA).
Campbell, S.D.; Olson, S.H.
This paper describes an artificial intelligence-based approach for automated recognition of wind shear hazards. The design of a prototype system for recognizing low-altitude wind shear events from Doppler radar displays is presented. This system, called WX1, consists of a conventional expert system augmented by a specialized capability for processing radar images. The radar image processing component of the system employs numerical and computer vision techniques to extract features from radar data. The expert system carries out symbolic reasoning on these features using a set of heuristic rules expressing meteorological knowledge about wind shear recognition. Results are provided demonstrating the ability of the system to recognize microburst and gust front wind shear events. 11 references.
for interpreting the interaction of the radar energy with the cloud. Point values of the liquid-water concentration are estimated from measurements of the received power. The measurements were made under conditions which minimized errors arising from attenuation...
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.
Cloppet, E.; Regimbeau, M.
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.
Neyland, Michael Arthur
of Eq (4) is 2 log Z = 2 log r + log P ? log C~k~ e r (8) Using the values of C for the TA"}U radar- given below and that of 2 ~k~ given earlier, we have C = 1. 0089 x 10 3 C = 8. 609 x 10 Iog C ski = 9. 0 2 log C lkl = 10. 1 2= (6a) (6})) By..., ubstituting Eq (6) into Eq (5) we get log Z = 2 log r + log P + 9. 0 e3 r log Z = 2 log r + log P + 10. 1 e10 r (7a) (7b) The digital value of P is converted to its dBm equivalent (always r negative) through the use of calibration data for each...
Danz, Mari E.; Corsi, Steven; Brooks, Wesley R.; Bannerman, Roger T.
Understanding the response of total suspended solids (TSS) and total phosphorus (TP) to influential weather and watershed variables is critical in the development of sediment and nutrient reduction plans. In this study, rainfall and snowmelt event loadings of TSS and TP were analyzed for eight agricultural watersheds in Wisconsin, with areas ranging from 14 to 110 km2 and having four to twelve years of data available. The data showed that a small number of rainfall and snowmelt runoff events accounted for the majority of total event loading. The largest 10% of the loading events for each watershed accounted for 73–97% of the total TSS load and 64–88% of the total TP load. More than half of the total annual TSS load was transported during a single event for each watershed at least one of the monitored years. Rainfall and snowmelt events were both influential contributors of TSS and TP loading. TSS loading contributions were greater from rainfall events at five watersheds, from snowmelt events at two watersheds, and nearly equal at one watershed. The TP loading contributions were greater from rainfall events at three watersheds, from snowmelt events at two watersheds and nearly equal at three watersheds. Stepwise multivariate regression models for TSS and TP event loadings were developed separately for rainfall and snowmelt runoff events for each individual watershed and for all watersheds combined by using a suite of precipitation, melt, temperature, seasonality, and watershed characteristics as predictors. All individual models and the combined model for rainfall events resulted in two common predictors as most influential for TSS and TP. These included rainfall depth and the antecedent baseflow. Using these two predictors alone resulted in an R2 greater than 0.7 in all but three individual models and 0.61 or greater for all individual models. The combined model yielded an R2 of 0.66 for TSS and 0.59 for TP. Neither the individual nor the combined models were substantially improved by using additional predictors. Snowmelt event models were statistically significant for individual and combined watershed models, but the model fits were not all as good as those for rainfall events (R2 between 0.19 and 0.87). Predictor selection varied from watershed to watershed, and the common variables that were selected were not always selected in the same order. Influential variables were commonly direct measures of moisture in the watershed such as snowmelt, rainfall + snowmelt, and antecedent baseflow, or measures of potential snowmelt volume in the watershed such as air temperature.
Graaf, Martin de
Large-scale bird migration monitoring using operational weather radar M. de Graafa, H. Leijnsea Monitoring of bird migration is extremely important for military aviation (see Figure 1), ecology, and disease control. Operational weather radars are promising tools for obtaining information on bird
Haines, Stephanie L.
gauge network can also be used to help validate remotely sensed measurements of rainfall, soil moisture to validate weather radar and lightning data, monitor spatial distributions of precipitation for soil moisture outreach activity by directly involving the Huntsville community in a NASA activity. Expansion
Siu-yeung Cho; Tommy W. S. Chow
At the moment, weather forecasting is still an art — the experience and intuition of forecasters play a significant role in determining the quality of forecasting. This paper describes the development of a new approach to rainfall forecasting using neural networks. It deals with the extraction of information from radar images and an evaluation of past rain gauge records to
Liechti, Kaethi; Knechtl, Valentin; Andres, Norina; Sideris, Ioannis; Zappa, Massimiliano
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 models.
Meneghini, R.; Liao, L.
In writing the integral equations for the median mass diameter and number concentration, or comparable parameters of the raindrop size distribution, it is apparent that the forms of the equations for dual-polarization and dual-wavelength radar data are identical when attenuation effects are included. The differential backscattering and extinction coefficients appear in both sets of equations: for the dual-polarization equations, the differences are taken with respect to polarization at a fixed frequency while for the dual-wavelength equations, the differences are taken with respect to frequency at a fixed polarization. An alternative to the integral equation formulation is that based on the k-Z (attenuation coefficient-radar reflectivity factor) parameterization. This-technique was originally developed for attenuating single-wavelength radars, a variation of which has been applied to the TRMM Precipitation Radar data (PR). Extensions of this method have also been applied to dual-polarization data. In fact, it is not difficult to show that nearly identical equations are applicable as well to dualwavelength radar data. In this case, the equations for median mass diameter and number concentration take the form of coupled, but non-integral equations. Differences between this and the integral equation formulation are a consequence of the different ways in which attenuation correction is performed under the two formulations. For both techniques, the equations can be solved either forward from the radar outward or backward from the final range gate toward the radar. Although the forward-going solutions tend to be unstable as the attenuation out to the range of interest becomes large in some sense, an independent estimate of path attenuation is not required. This is analogous to the case of an attenuating single-wavelength radar where the forward solution to the Hitschfeld-Bordan equation becomes unstable as the attenuation increases. To circumvent this problem, the equations can be expressed in the form of a final-value problem so that the recursion begins at the far range gate and proceeds inward towards the radar. Solving the problem in this way traditionally requires estimates of path attenuation to the final gate: in the case of orthogonal linear polarizations, the attenuations at horizontal and vertical polarizations (same frequency) are required while in the dual-wavelength case, attenuations at the two frequencies (same polarization) are required.
Wang, Xianwei; Xie, Hongjie; Sharif, Hatim; Zeitler, Jon
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%).
POLARIZATION RADAR ROBIN J. HOGAN Department of Meteorology, University of Reading, United Kingdom ABSTRACT and dp. The scheme is tested on S-band radar data from Southern England in cases of rain, spherical hail to refine rain rate estimates. Corresponding author address: Department of Meteorology, Earley Gate, PO Box
An examination of 60 years of rainfall during three months of the cane-harvesting season has shown a reduction of rainfall at inland stations coinciding with increasing cane production; no such reduction occurred at a `control' station upwind of smoke from the cane fires. The reduction is consistent with the hypothesis that through their activity as condensation nuclei the smoke particles
Young, Steven D.; deHaag, Maatren Uijt
Flight in Instrument Meteorological Conditions requires pilots to manipulate flight controls while referring to a Primary Flight Display. The Primary Flight Display indicates aircraft attitude along with, in some cases, many other state variables such as altitude, speed, and guidance cues. Synthetic Vision Systems have been proposed that overlay the traditional information provided on Primary Flight Displays onto a scene depicting the location of terrain and other geo-spatial features.Terrain models used by these displays must have sufficient quality to avoid providing misleading information. This paper describes how X-band radar measurements can be used as part of a monitor, and/or maintenance system, to quantify the integrity of terrain models that are used by systems such as Synthetic Vision. Terrain shadowing effects, as seen by the radar, are compared in a statistical manner against estimated shadow feature elements extracted from the stored terrain model from the perspective of the airborne observer. A test statistic is defined that enables detection of errors as small as the range resolution of the radar. Experimental results obtained from two aircraft platforms hosting certified commercial-off-the-shelf X-band radars test the premise and illustrate its potential.
Pineda, Luis; Willems, Patrick
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.
Graaf, Martin de
1 The FlySafe project: How weather radars can improve the en-route bird strike warning system. Hans Graaf3 and Willem Bouten1 In civil aviation the majority of bird strikes occur below 1000 ft, thus civil bird strikes predominantly occur on and around aerodromes. In military aviation, however, the problem
Hohl, Roman; Schiesser, Hans-Heinrich; Knepper, Ingeborg
As the first of its kind, this study presents damage functions between two damage variables of hail-damaged automobiles and radar-derived hail kinetic energy for a total of 12 severe hailstorms that have occurred over the Swiss Mittelland (1992-1998). Hail kinetic energy is calculated from C-band Doppler radar CAPPIs at low storm level (1.5 km MSL) and is integrated per radar element ( EKINPIX) for entire hail cells. Hail damage claim data were available per Swiss community on a daily basis and transformed (Delaunay triangulation) along with EKINPIX to a regular 3×3 km grid, thereafter allowing cross-correlation between the variables. The results show nonlinear relationships between EKINPIX and both loss ratios and mean damages per hail-damaged car, differing between high hail season storms (15 June-15 August) and storms that occurred during the low season (before and after). A weighted logistic function provides correlation coefficients between EKINPIX and loss ratios of 0.71 (0.79) for high (low) season storms and 0.76 (0.40) for mean damages of high (low) season hailstorms. Maximally possible loss ratios reach 60% (40%) in high (low) season storms with maximum mean damages of CHF 6000 (CHF 3000) and average values around CHF 3100 (CHF 2100). Seasonal differences in hailfall intensities are discussed in terms of atmospheric conditions favoring convective activity and the likelihood of higher numbers of large hailstones (>20 mm in diameter) that induce more severe damage to cars during the high storm season. The results suggest that radar-derived hail kinetic energy could be used by insurance companies in the future to (1) assess hail damage to cars immediately after a storm has passed over a radar observation area and (2) to estimate potential maximal hail losses to car portfolios for parts of central Europe.
Schneider, David J.; Hoblitt, Richard P.
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.
Nesbitt, Stephen W.; Zipser, Edward J.; Kummerow, Christian D.
An evaluation of the version-5 precipitation radar (PR; algorithm 2A25) and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI; algorithm 2A12) rainfall products is performed across the Tropics in two ways: 1) by comparing long-term TRMM rainfall products with Global Precipitation Climatology Centre (GPCC) global rain gauge analyses and 2) by comparing the rainfall estimates from the PR and TMI on a rainfall feature-by-feature basis within the narrow swath of the PR using a 1-yr database of classified precipitation features (PFs). The former is done to evaluate the overall biases of the TMI and PR relative to “ground truth” to examine regional differences in the estimates; the latter allows a direct comparison of the estimates with the same sampling area, also identifying relative biases as a function of storm type. This study finds that the TMI overestimates rainfall in most of the deep Tropics and midlatitude warm seasons over land with respect to both the GPCC gauge analysis and the PR (which agrees well with the GPCC gauges in the deep Tropics globally), in agreement with past results. The PR is generally higher than the TMI in midlatitude cold seasons over land areas with gauges. The analysis by feature type reveals that the TMI overestimates relative to the PR are due to overestimates in mesoscale convective systems and in most features with 85-GHz polarization-corrected temperature of less than 250 K (i.e., with a significant optical depth of precipitation ice). The PR tended to be higher in PFs without an ice-scattering signature of less than 250 K. Normalized for a subset of features with a large rain volume (exceeding 104 mm h-1 km2) independent of the PF classification, features with TMI > PR in the Tropics tended to have a higher fraction of stratiform rainfall, higher IR cloud tops, more intense radar profiles and 85-GHz ice-scattering signatures, and larger rain areas, whereas the converse is generally true for features with PR > TMI. Subtropical-area PF bias characteristics tended not to have such a clear relationship (especially over the ocean), a result that is hypothesized to be due to the influence of more variable storm environments and the presence of frontal rain. Melting-layer effects in stratiform rain and a bias in the ice-scattering rain relationship were linked to the TMI producing more rainfall than the PR. However, noting the distinct characteristic biases Tropics-wide by feature type, this study reveals that accounting for regime-dependent biases caused by the differing horizontal and vertical morphologies of precipitating systems may lead to a reduction in systematic relative biases in a microwave precipitation algorithm.
Young, Steve; UijtdeHaag, Maarten; Sayre, Jonathon
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.
SummaryImportant damages occur in small headwater catchments when they are hit by severe storms with complex spatio-temporal structure, sometimes resulting in flash floods. As these catchments are mostly not covered by sensor networks, it is difficult to forecast these floods. This is particularly true for road submersions, representing major concerns for flood event managers. The use of Quantitative Precipitation Estimates and Forecasts (QPE/QPF) especially based on radar measurements could particularly be adequate to evaluate rainfall-induced risks. Although their characteristic time and space scales would make them suitable for flash flood modelling, the impact of their uncertainties remain uncertain and have to be evaluated. The Gard region (France) has been chosen as case study. This area is frequently affected by severe flash floods, and an application devoted to the road network has also been recently developed for the North part of this region. This warning system combines distributed hydro-meteorological modelling and susceptibility analysis to provide warnings of road inundations. The warning system has been tested on the specific storm of the 29-30 September 2007. During this event, around 200 mm dropped on the South part of the Gard and many roads were submerged. Radar-based QPE and QPF have been used to forecast the exact location of road submersions and the results have been compared to the effective road submersions actually occurred during the event as listed by the emergency services. Used on an area it has not been calibrated, the results confirm that the road submersion warning system represents a promising tool for anticipating and quantifying the consequences of storm events at ground. It rates the submersion risk with an acceptable level of accuracy and demonstrates also the quality of high spatial and temporal resolution radar rainfall data in real time, and the possibility to use them despite their uncertainties. However because of the quality of rainfall forecasts falls drastically with time, it is not often sufficient to provide valuable information for lead times exceeding 1 h.
Toward the Assimilation of the Atmospheric Surface Layer Using Numerical Weather Prediction affected by negative refractivity gradients in the atmospheric surface layer, which form what is often of California, San Diego, La Jolla, California TED ROGERS Atmospheric Propagation Branch, Space and Naval
Overeem, A.; Leijnse, H.; Uijlenhoet, R.
Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.
Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko
Accurate measurements of rainfall are important in many hydrological applications, for instance, flash-flood early-warning systems, hydraulic structures design, agriculture, weather forecasting, and climate modelling. Rainfall intensities can be retrieved from (commercial) microwave link networks. Whenever possible, link networks measure and store the decrease in power of the electromagnetic signal at regular intervals. The decrease in power is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the physics involved in the measurements such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology, the spatial density of the network, and the availability of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of The Netherlands. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also to test the actual and optimal performance of one commercial microwave network from one of the cellular providers in The Netherlands.
Yokota, Toshiyuki; Inazaki, Tomio; Shinagawa, Shunsuke; Ueda, Takumi
This paper describes a three-dimensional ground penetrating radar (GPR) survey carried out around a levee of the Ara River in Saitama, Japan, where deformation of the ground was observed after heavy rainfall associated with the typhoon of September 2007. The high-density 3D GPR survey was conducted as a series of closely adjacent four directional sets of 2D surveys at an area surrounding vertical cracks on the paved road caused by deformations induced by heavy rain. The survey directions of the 2D surveys were 0, 90, 45, and -45 degrees with respect to the paved road and the intervals between lines were less than 0.5m. The 3D subsurface structure was accurately imaged by the result of data processing using Kirchhoff-type 3D migration. As a result, locations and vertical continuities of the heavy rainfall induced cracks in the paved road were clearly imaged. This will be a great help in considering the generation mechanisms of the cracks. Moreover, the current risk of a secondary disaster was found to be low, as no air-filled cavities were detected by the 3D GPR survey.
Bendix, Jörg; Rollenbeck, Rütger; Reudenbach, Christoph
The diurnal precipitation dynamics in an east-west-oriented valley that connects the Amazon lowlands and the inter-Andean basin of southern Ecuador (Rio San Francisco valley) is investigated by means of a K-band rain-radar profiler (located at the ECSF research station, latitude: 3° 58'S, longitude: 79° 4W) and additional remotely sensed data. A pre-dawn/dawn (5:30-6:30 LST) maximum of rainfall is found and a secondary peak is observed after noon (14:30-15:30 LST). Although the frequency distribution of rain rates reveals that a great portion of rainfall is of stratiform character, vertical profiles of rain rate and droplet concentration points to the important contribution of embedded convection and/or showers produced by local heating for the overall amount of rainfall. Specific differences in stratification and process dynamics could be found for both peak times. The pre-dawn maximum can be related to mesoscale instabilities over the Peruvian Amazon close to the south Ecuadorian border. Extended cold air drainage flow from the Andes and low-level confluence due to the concavity of the Andean chain in this area leads to convective instability in the nocturnal Amazonian boundary layer, which is extended to the study area by the predominant easterlies in the mid-troposphere. Rain clouds with at least embedded shallow convection can overflow the bordering ridges of the San Francisco valley providing rains of higher intensity at the ECSF research station. On the contrary, the afternoon convective precipitation can be caused by locally induced thermal convection at the bordering slopes (up-slope breeze system) where the ECSF station profits from precipitation off the edge of these local cells due to the narrow valley.
In the project you will learn about thunderstorms and tornadoes and play a weather matching game. What exactly are thunderstorms and tornadoes? Use your T- chart to explain some facts about a thunderstorm and a tornado as we review each. T-Chart Begin by reviewing what a thunderstorm is and how they form. Thunderstorm information What is a thunderstorm? What are thunderstorms most likely to occur? What causes thunder? Next review what a tornado ...
Over the past few decades, several single radar methods have been developed to probe the kinematic structure of storms. All these methods trade angular-resolution to retrieve the wind-field. To date, the spaced-antenna method has been employed for profiling the ionosphere and the precipitation free lower atmosphere. This work focuses on applying the spaced-antenna method on an X-band active phased-array radar for high resolution horizontal wind-field retrieval from precipitation echoes. The ability to segment the array face into multiple displaced apertures allows for flexible spaced-antenna implementations. The methodology employed herein comprises of Monte-Carlo simulations to optimize the spaced-antenna system design and analysis of real data collected with the designed phased-array system. The contribution that underpins this dissertation is the demonstration of qualitative agreement between spaced-antenna and Doppler beam swinging retrievals based on real data. First, simulations of backscattered electric fields at the antenna array elements are validated using theoretical expressions. Based on the simulations, the degrees of freedom in the spaced-antenna system design are optimized for retrieval of mean baseline wind. We show that the designed X-band spaced-antenna system has lower retrieval uncertainty than the existing S-band spaced-antenna implementation on the NWRT. This is because of the flexibility to synthesize small overlapping apertures and the ability to obtain statistically independent samples at a faster rate at X-band. We then demonstrate a technique to make relative phase-center displacement measurements based on simulations and real data from the phased-array spaced-antenna system. This simple method uses statistics of precipitation echoes and apriori beamwidth measurements to make field repeatable phase-center displacement measurements. Finally, we test the hypothesis that wind-field curvature effects are common to both the spaced-antenna and Doppler beam swinging methods. Based on a close-range winter storm data set, we find that the spaced-antenna and fine-resolution Doppler beam swinging retrievals are in qualitative agreement. The correlation between the spaced-antenna and fine-resolution Doppler beam swinging retrievals was 0.57. The lowered correlation coefficient was, in part, due to the high standard deviation of the DBS retrievals. At high wind-speeds, the spaced-antenna retrievals significantly departed from variational retrievals of mean baseline wind.
Liu, Jia; Bray, Michaela; Han, Dawei
Mesoscale Numerical Weather Prediction (NWP) models are nowadays gaining more and more attention in providing high-resolution rainfall forecasts for real-time flood forecasting. In this study, the newest generation NWP model, Weather Research & Forecasting (WRF) model, is integrated with the rainfall-runoff model in real-time to generate accurate flow forecasts at the catchment scale. The rainfall-runoff model is chosen as the Probability Distribution Model (PDM), which has widely been used for flood forecasting. Dual data assimilation is carried out for real-time updating of the flood forecasting system. The 3-Dimensional Variational (3DVar) data assimilation scheme is incorporated with WRF to assimilate meteorological observations and weather radar reflectivity data in order to improve the WRF rainfall forecasts; meanwhile real-time flow observations are assimilated by the Auto-Regressive Moving Average (ARMA) model to update the forecasted flow transformed by PDM. The Brue catchment located in Southwest England with a drainage area of 135.2 km2 is chosen to be the study area. A dense rain gauge network was set up during a project named HYREX (Hydrological radar experiment), which contains 49 rain gauges and a C-band weather radar, providing with sufficient hydrological and radar data for WRF model verification and data assimilation. Besides the radar reflectivity data, two types of NCAR archived data (SYNOP and SOUND, http://dss.ucar.edu) are also assimilated by 3DVar, which provide real-time surface and upper-level observations of pressure, temperature, humidity and wind from fixed and mobile stations. Four 24 hour storm events are selected from the HYREX project with different characteristics regarding storm formation and rainfall-runoff responses. Real-time flood forecasting is then carried out by the constructed forecasting system for the four storm events with a forecast lead time of 12 hours. The forecasting accuracy of the whole system is found to be largely improved by incorporating the WRF forecasted rainfall when the forecast lead time is beyond the catchment concentration time. The assimilation of real-time meteorological and radar data also show great advantage in improving the performance of the flood forecasting system. Key words: real-time flood forecasting; Weather Research & Forecasting (WRF) model; high-resolution rainfall forecasts; dual data assimilation.
Hinton, David A.
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.
Mahmoudzadeh, M. R.; Francés, A. P.; Lubczynski, M.; Lambot, S.
Precise and non-invasive measurement of groundwater depth is essential to support management of groundwater resources. In that respect, GPR is a promising tool for high resolution, large scale characterization and monitoring of hydrological systems. We applied GPR in a semi-arid catchment (Sardon, Salamanca, Spain) in order to investigate the water table depth in weathered granites. We used a pulse radar with a single 200 MHz bowtie antenna combined with a differential GPS and a survey wheel for accurate positioning. Measurements were performed following a series of transects crossing perpendicularly the bed of the Sardon streams, which were dry during the survey period (September 2009). In order to transform the GPR data from time to depth we estimated the soil dielectric constant using frequency domain reflectometry (FDR) or water level depth information from several observation wells. Electrical resistivity tomography (ERT) was applied along the GPR profiles and compared to the GPR results. GPR signals were also simulated using forward modeling (GprMax2D) of several hypothetic configurations of the subsurface. Those techniques helped us to better understand and interpret the GPR data. In general, the shallow water table was sparsely detected in the GPR profiles ranging from ˜ 1 to ˜ 3 meters the entire catchment. The results showed a good agreement of ERT and GPR profiles. The comparison of measured and simulated GPR data showed multiple reflections in presence of the saturated fractured granite.
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...
Overeem, A.; Leijnse, H.; Uijlenhoet, R.
Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information. Many countries do not have continuously operating weather radars, and have no or few rain gauges. A new development is rainfall estimation from microwave links of commercial cellular telecommunication networks. Such networks cover large parts of the land surface of the earth and have a high density, especially in urban areas. The estimation of rainfall using commercial microwave links could therefore become a valuable source of information. The data produced by microwave links is essentially a by-product of the communication between mobile telephones. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (1500) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both calibration and validation are done using gauge-adjusted radar data. Validation results reveal that relatively accurate country-wide rainfall maps can be obtained from microwave link data. Since cellular telephone networks are used worldwide, data from such networks could also be used to obtain rainfall maps over larger areas and in areas where no other sources of rainfall data are available.
This undergraduate meteorology tutorial from Texas A&M University discusses the basic principles of operation of weather radars, describes how to interpret radar mosaics, and discusses the use of radar in weather forecasting. Students learn the relationship between range and elevation and how to use radar images and mosaics in short-range forecasting.
Hazenberg, P.; Torfs, P. J. J. F.; Leijnse, H.; Uijlenhoet, R.
The wide scale implementation of weather radar systems over the last couple of decades has increased our understanding concerning spatio-temporal precipitation dynamics. However, the quantitative estimation of precipitation by these devices is affected by many sources of error. A very dominant source of error results from vertical variations in the hydrometeor size distribution known as the vertical profile of reflectivity (VPR). Since the height of the measurement as well as the beam volume increases with distance from the radar, for stratiform precipitation this results in a serious underestimation (overestimation) of the surface reflectivity while sampling within the snow (bright band) region. This research presents a precipitation cell-based implementation to correct volumetric weather radar measurements for VPR effects. Using the properties of a flipping carpenter square, a contour-based identification technique was developed, which is able to identify and track precipitation cells in real time, distinguishing between convective, stratiform and undefined precipitation. For the latter two types of systems, for each individual cell, a physically plausible vertical profile of reflectivity is estimated using a Monte Carlo optimization method. Since it can be expected that the VPR will vary within a given precipitation cell, a method was developed to take the uncertainty of the VPR estimate into account. As a result, we are able to estimate the amount of precipitation uncertainty as observed by weather radar due to VPR for a given precipitation type and storm cell. We demonstrate the possibilities of this technique for a number of winter precipitation systems observed within the Belgian Ardennes. For these systems, in general, the precipitation uncertainty estimate due to vertical reflectivity profile variations varies between 10-40%.
Suarez Hincapie, J. N.
Manizales is a city located in west-central Colombian Andes in the Caldas province, whose spatial location coincides with one of the most threatened areas of Colombia (landslides, earthquakes, volcanic eruptions, other). As a middle Andean mountainous city and for being located in the area of influence of the ITCZ presents an equatorial mountain climate with a bimodal rainfall regime, and with an average annual rainfall around 2000 mm, it shows very significant rates of precipitation, on average, 70% of the days of the year it is rainy. This situation favors the formation of large masses of clouds and the presence of macroclimatic phenomena such as ENSO, which has historically caused large-scale impacts in both warm and cold phase. Since last decade different entities have implemented a hydro-meteorological network which measures and transmits telemetrically every five minutes hydro-climatic variables. In general, the real-time weather monitoring should be used for a better understanding of our environmental urban environment and to establish indicators of quality of life and welfare for the community. Despite the city has telemetric data on atmospheric and hydrological variables, there is still no tool or a methodology able to generate a spatio-temporal description of these variables. So, the aim of this work is to establish guidelines to sort all this information of atmospheric variables monitored in real time with the help of data mining techniques, machine learning tools to improve the knowledge of atmospheric patterns at Manizales and to serve for territorial planning and decision makers. To reach this purpose the current data warehouse available at the National University of Colombia at Manizales will be used, and it will be fed with observed variables from hydro-meteorological monitoring stations that transmit in real-time. Then, as mentioned this information will make the corresponding processing with data mining techniques to describe the rainfall patterns. All this complemented with the application of statistical techniques for data analysis and exploration. The main contribution of this research is the creation of tools to be used in numerical modeling with forecasting purposes, aiming to improve the resolution given by mesoscale models, which are currently used for weather forecast in Colombia.
Ma, S.; Rodó, X.; Song, Y.; Cash, B. A.
The Indian summer monsoon rainfall (ISMR) over the Western Ghats (WG) and the Bay of Bengal (BoB) is marked by the intraseasonal oscillations (ISOs) with preferred 10-20-day and 30-50-day bands. On the basis of pentad Climate Prediction Center Merged Analysis Precipitation and daily sea level pressure and winds at 850 hPa derived from European Center for Medium-range Weather Forecast reanalysis, we present the structure and evolution of the ISOs linked to the ISMR variations over the WG and the BoB and the associated anomalies of the atmospheric circulation using the approaches of wavelet analysis, bandpass filtering and composite analysis. This study reveals that the activities of both the intertropical convergence zone (ITCZ) and the western Pacific subtropical high (WPSH) contribute strongly to the structure and propagation of the ISOs on intraseasonal time scales. Northward development and propagation of the ITCZ plays a critical role in the northward-propagating ISOs, but not in the westward-propagating BoB 10-20-day ISOs. The latter ISOs may be linked, instead, to the activity of synoptic-scale weather systems to the east over the western tropical Pacific. The enhanced ITCZ in the tropical Indian Ocean plays a strong role in the sudden strengthening of the WPSH during the transition from the break to active phase of the 30-50-day ISOs. We find that the strong WPSH in the Asian summer monsoon season, with generally northward advance and eastward withdrawal, promotes the formation of a northwest to southeast tilted anomalous rainfall belt over the East Asian tropical summer monsoon region and the western tropical Pacific in the 30-50-day low-frequency band. Positive (Negative) elongated rainfall anomalies with an unbroken northwest-southeast tilt, strong easterly (westerly) anomalies in the tropical Pacific, and northward advance and eastward movement of strong (weak) WPSH are favorable for maintaining the eastward propagation of the 30-50-day ISOs in the Pacific. Daily high-resolution sea surface temperature obtained from the National Oceanic and Atmospheric Administration is used to explain the propagation features of the 10-20-day ISOs in the Indian Ocean.
Hürlimann, Marcel; Abancó, Clàudia; Moya, Jose; Berenguer, Marc
Empirical rainfall thresholds are a widespread technique in debris-flow hazard assessment and can be established by statistical analysis of historic data. Typically, data from one or several rain gauges located nearby the affected catchment is used to define the triggering conditions. However, this procedure has been demonstrated not to be accurate enough due to the spatial variability of convective rainstorms. In 2009, a monitoring system was installed in the Rebaixader catchment, Central Pyrenees (Spain). Since then, 28 torrential flows (debris flows and debris floods) have occurred and rainfall data of 25 of them are available with a 5-minutes frequency of recording ("event rainfalls"). Other 142 rainfalls that did not trigger events ("no event rainfalls) were also collected and analysed. The goal of this work was threefold: a) characterize rainfall episodes in the Rebaixader catchment and compare rainfall data that triggered torrential events and others that did not; b) define and test Intensity-Duration (ID) thresholds using rainfall data measured inside the catchment; c) estimate the uncertainty derived from the use of rain gauges located outside the catchment based on the spatial correlation depicted by radar rainfall maps. The results of the statistical analysis showed that the parameters that more distinguish between the two populations of rainfalls are the rainfall intensities, the mean rainfall and the total precipitation. On the other side, the storm duration and the antecedent rainfall are not significantly different between "event rainfalls" and "no event rainfalls". Four different ID rainfall thresholds were derived based on the dataset of the first 5 years and tested using the 2014 dataset. The results of the test indicated that the threshold corresponding to the 90% percentile showed the best performance. Weather radar data was used to analyse the spatial variability of the triggering rainfalls. The analysis indicates that rain gauges outside the catchment may be considered useful or not to describe the rainfall depending on the type of rainfall. For widespread rainfalls, further rain gauges can give a reliable measurement, because the spatial correlation decreases slowly with the distance between the rain gauge and the debris-flow initiation area. Contrarily, local storm cells show higher space-time variability and, therefore, representative rainfall measurements are obtained only by the closest rain gauges. In conclusion, the definition of rainfall thresholds is a delicate task. When the rainfall records are coming from gauges that are outside the catchment under consideration, the data should be carefully analysed and crosschecked with radar data (especially for small convective cells).
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.
Fang, N.; Bedient, P. B.
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.
Fink, A. H.; van der Linden, R.; Phan-Van, T.; Pinto, J. G.
About 85% of the annual precipitation in southern Vietnam (ca. 8-12°N, 104-110°E) occurs during the southwest monsoon season (June to October). Large-scale equatorial waves like the Madden-Julian Oscillation (MJO) and Convectively Coupled Equatorial Waves (CCEWs) are known to modulate the large-scale convective activity, often indicated by variations in (filtered) satellite-observed outgoing longwave radiation (OLR) anomalies. The present contribution analyses and quantifies the role of the MJO and CCEWs for rainfall not only in southern and central Vietnam as a whole, but also for smaller climatological sub-regions. Using circum-equatorial NOAA OLR (15°S-15°N), prominent spectral peaks are identified in wavenumber-frequency diagrams along the dispersion curves for the solutions of the shallow water equations. They are interpreted as CCEWs. Meridionally averaged wave-filtered OLR and its time derivatives are used to define phases and amplitudes of CCEWs. This will allow determining active and inactive phases of CCEWs in the vicinity of Vietnam. Eastward propagating deep convection is also related to the 30-90-day MJO. The OLR MJO Index (OMI) is used for the definition of convectively active and inactive phases of the MJO. TRMM 3B42 V7, APHRODITE MA V1101 data, and rain gauge measurements are used to investigate the relation between tropical wave phases and amplitudes and precipitation in southern and central Vietnam and adjacent regions. Results using the OMI are compared with those using the Real-time Multivariate MJO (RMM) Index. The major findings are: (a) Precipitation amounts in southern Vietnam are higher during convectively active phases of the MJO and CCEWs. The waves differ in terms of their relative importance for rainfall enhancement. (b) For increasing CCEW amplitudes, the difference between area-averaged precipitation during inactive and active phases increases. We provide evidence that precipitation amounts are higher when multiple wave types are in their convectively active phases over the Vietnam region.
Souvignet, M.; Freer, J. E.; de Almeida, G. A.; Coxon, G.; Neal, J. C.; Champion, A.; Cloke, H. L.; Bates, P. D.
Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade is still poorly understood. Such a project requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and hydraulic flood wave propagation based on the runoff predictions. Accounting for uncertainty in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures as part of the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions which are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated. The study is performed in the Severn catchment over summer 2007, where a series of large rainfall events (over 100mm between the 20th and 21rst of July in certain sub-catchments) caused record floods in the study area. Differences in water level at benchmark stations are compared and the resulting prediction uncertainties are analysed for the different rainfall products. These results quantify how different cascading techniques and rainfall input uncertainty affects the resultant set of behavioural simulations. This allows us to compare the performance of different rainfall products for real forecasting situations.
Schulz, J.; Bauer, P.; Simmer, C.
Rainfall estimation from satellite data over land surfaces still represents a challenge because neither at visible/infrared nor at microwave wavelengths do raindrops provide significant contributions to the total signal to allow a direct estimation of rain rate. The proposed algorithm consists of a two-stage approach to distinguish precipitation signatures from other effects: (1) Contributions from slowly varying parameters (surface type and state) are isolated by comparing observed brightness temperatures to those obtained from previous orbits only containing rain free observations. (2) Effects of more dynamic parameters, i.e. surface temperature and moisture, are reduced by means of principal component analysis. The general signatures of temperature and moisture variations are deduced from radiative transfer simulations. The technique is first applied to TRMM's TMI measurements where rain rates and rain water contents are estimated by using co-located PR measurements to effectively calibrate the microwave precipitation index. A comparison to TRMM standard products shows that the algorithm has an improved potential for the detection of light rain with rain rates less than 2 mm/h. The detection part of the algorithm has also been applied to SSM/I data, revealing almost the same detection skill as for the TMI. To transfer the calibration using the PR to the SSM/I, the TMI is used to simulate measurements of the SSM/I by co-location of TMI and PR pixels using the viewing geometry of the SSM/I.
Rios Gaona, M. F.; Overeem, A.; Leijnse, H.; Uijlenhoet, R.
Accurate measurements of rainfall are important in many hydrological and meteorological applications, for instance, flash-flood early-warning systems, hydraulic structures design, irrigation, weather forecasting, and climate modelling. Whenever possible, link networks measure and store the received power of the electromagnetic signal at regular intervals. The decrease in power can be converted to rainfall intensity, and is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfils the continuous effort to obtain measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e. the errors involved in link rainfall retrievals, such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, dry weather baseline attenuation, quantization of the received power, drop size distribution (DSD), and multi-path propagation; and (2) those associated with mapping, i.e. the combined effect of the interpolation methodology and the spatial density of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of the Netherlands. Simulated link rainfall depths refer to path-averaged rainfall depths obtained from radar data. The ~ 3500 real and simulated rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify and quantify the sources of uncertainty in such rainfall maps, but also test the actual and optimal performance of one commercial microwave network from one of the cellular providers in the Netherlands. Errors in microwave link measurements were found to be the source that contributes most to the overall uncertainty.
and reflectivity are presented to a neural network that12 was trained on historical data. The neural network of a widespread7 polarimetric S-band radar network in the United States, it has become possible to fully utilize827 by non-meteorological radar echoes such as insects, birds, sun spikes, test patterns, ground28 1
Valters, Declan; Brocklehurst, Simon; Schultz, David
The dynamics of severe storms have a pronounced effect on the temporal and spatial distribution of water input to river catchments in upland environments, particularly those with complex orography and steep topographic gradients. Existing landscape evolution models typically forsake realistic patterns of rainfall during storm events, in favour of uniform rainfall input. It is demonstrated that this simplification fails to resolve localised areas of flooding and erosion within a drainage basin, despite the known significance of erosion thresholds and orographic enhancement of rainfall. This shortfall can be remedied by the incorporation of high-resolution precipitation data from rainfall radar into model simulations, accounting for sub-catchment-scale variation in precipitation patterns. Using a series of simulations with both synthetic and real topographies, it is shown that there is a wide variation in hydro-geomorphic response observed in comparison to simulations with spatially-averaged rainfall: localised water depths and erosion rates vary by up to an order of magnitude within the catchments studied. The real-data examples, chosen from severe UK rainfall events over the last 10 years, are analysed by combining the CAESAR-Lisflood landscape evolution model at 5m resolution with data from the UK Met Office NIMROD rainfall radar at 1km resolution. The model-coupling framework presented is also suited to using output from weather forecasting models. The applications are wide-ranging, from improving the accuracy of hydrological predictions during single storm events, to understanding longer-term evolution of catchment-scale geomorphology.
Feaster, Toby D.; Westcott, Nancy E.; Hudson, Robert J.M.; Conrads, Paul A.; Bradley, Paul M.
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 total measured rainfall at the NWS COOP locations, this bias would be expected. Therefore, to better assess the use of NEXRAD-based rainfall estimates as compared to NWS COOP rainfall data on the hydrologic simulations, TOPMODEL was recalibrated and updated simulations were made using the NEXRAD-based rainfall data. Comparisons of observed and simulated streamflow show that the TOPMODEL results using measured rainfall data and NEXRAD-based rainfall are comparable. Nonetheless, TOPMODEL simulations using NEXRAD-based rainfall still tended to underpredict total streamflow volume, although the magnitude of differences were similar to the simulations using measured rainfall. The McTier Creek watershed was subdivided into 12 subwatersheds and NEXRAD-based rainfall data were generated for each subwatershed. Simulations of streamflow were generated for each subwatershed using NEXRAD-based rainfall and compared with subwatershed simulations using measured rainfall data, which unlike the NEXRAD-based rainfall were the same data for all subwatersheds (derived from a weighted average of the six NWS COOP stations surrounding the basin). For the two simulations, subwatershed streamflow were summed and compared to streamflow simulations at two U.S. Geological Survey streamgages. The percentage differences at the gage near Monetta, South Carolina, were the same for simulations using measured rainfall data and NEXRAD-based rainfall. At the gage near New Holland, South Carolina, the percentage differences using the NEXRAD-based rainfall were twice as much as those using the measured rainfall. Single-mass curve comparisons showed an increase in the total volume of rainfall from north to south. Similar comparisons of the measured rainfall at the NWS COOP stations showed similar percentage differences, but the NEXRAD-based rainfall variations occurred over a much smaller distance than the measured rainfall. Nonetheless, it was concluded that in some cases, using NEXRAD-based rainfall data in TOPMODEL streamflow simulations may provide an effective alternative to using measured rainfa
) Doppler Radar and Weather Observations Academic Press, Second Edition (1992) Skolnik (1980) Radar SystemsRadar MeteorologyRadar Meteorology Feb 20, 1941 10 cm (S-band) radar used to track rain showers similar observations in the early 1940's (U.S. Air Corps meteorologists receiving "radar" training at MIT
Tanelli, Simone; Im, Eastwood
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.
Rauniyar, Surendra P.; Walsh, Kevin J. E.
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.
Anagnostou, Marios; Kalogiros, John; Nikolopoulos, Efthymios; Anagnostou, Emmanouil; Marra, Francesco; Mair, Elisabeth; Bertolidi, Giacomo; Tappeiner, Ulrike; Borga, Marco
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.
Shepherd, J. Marshall; Pierce, Harold F.; Negri, Andrew
Data from the Tropical Rainfall Measuring Mission's (TRMM) Precipitation Radar (PR) were employed to identify warm season rainfall (1998-2000) patterns around Atlanta, Montgomery, Nashville, San Antonio, Waco, and Dallas. Results reveal an average increase of -28% in monthly rainfall rates within 30-60 kilometers downwind of the metropolis with a modest increase of 5.6% over the metropolis. Portions of the downwind area exhibit increases as high as 51%. The percentage changes are relative to an upwind control area. It was also found that maximum rainfall rates in the downwind impact area exceeded the mean value in the upwind control area by 48% - 116%. The maximum value was generally found at an average distance of 39 km from the edge of the urban center or 64 km from the center of the city. Results are consistent with METROMEX studies of St. Louis almost two decades ago and with more recent studies near Atlanta. Future work is extending the investigation to Phoenix, Arizona, an arid U.S. city, and several international cities like Mexico City, Johannesburg, and Brasilia. The study establishes the possibility of utilizing satellite-based rainfall estimates for examining rainfall modification by urban areas on global scales and over longer time periods. Such research has implications for weather forecasting, urban planning, water resource management, and understanding human impact on the environment and climate.
Markewitz, Daniel; Resende, Julio C. F.; Parron, Lucilia; Bustamante, Mercedes; Klink, Carlos A.; Figueiredo, Ricardo De O.; Davidson, Eric A.
The cerrados of Brazil cover 2 million km2. Despite the extent of these seasonally dry ecosystems, little watershed research has been focused in this region, particularly relative to the watersheds of the Amazon Basin. The cerrado shares pedogenic characteristics with the Amazon Basin in draining portions of the Brazilian shield and in possessing Oxisols over much of the landscape. The objective of this research was to quantify the stream water geochemical relationships of an undisturbed 1200 ha cerrado watershed for comparison to river geochemistry in the Amazon. Furthermore, this undisturbed watershed was used to evaluate stream discharge versus dissolved ion concentration relationships. This research was conducted in the Córrego Roncador watershed of the Reserva Ecológica do Roncador (RECOR) of the Instituto Brasileiro Geografia e Estatística (IBGE) near Brasilia, Brazil. Bulk precipitation and stream water chemistry were analysed between May 1998 and May 2000. The upland soils of this watershed are nutrient poor possessing total stocks of exchangeable elements in the upper 1 m of 81 +/- 13, 77 +/- 4, 25 +/- 3, and 1 +/- 1 kg ha-1 of K, Ca, Mg, and P, respectively. Bulk precipitation inputs of dissolved nutrients for this watershed are low and consistent with previous estimates. The nutrient-poor soils of this watershed, however, increase the relative importance of precipitation for nutrient replenishment to vegetation during episodes of ecosystem disturbance. Stream water dissolved loads were extremely dilute with conductivities ranging from 4 to 10 ?S cm-1 during periods of high- and low-flow, respectively. Despite the low concentrations in this stream, geochemical relationships were similar to other Amazonian streams draining shield geologies. Discharge-concentration relationships for Ca and Mg in these highly weathered soils developed from igneous rocks of the Brazilian shield demonstrated a significant negative relationship indicating a continued predominance of groundwater baseflow contributions these cationic elements.
Bruni, G.; Reinoso, R.; van de Giesen, N. C.; Clemens, F. H. L. R.; ten Veldhuis, J. A. E.
Cities are increasingly vulnerable to floods generated by intense rainfall, because of urbanisation of flood-prone areas and ongoing urban densification. Accurate information of convective storm characteristics at high spatial and temporal resolution is a crucial input for urban hydrological models to be able to simulate fast runoff processes and enhance flood prediction in cities. In this paper, a detailed study of the sensitivity of urban hydrodynamic response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar were used as input into a detailed hydrodynamic sewer model for an urban catchment in the city of Rotterdam, the Netherlands. The aim was to characterise how the effect of space and time aggregation on rainfall structure affects hydrodynamic modelling of urban catchments, for resolutions ranging from 100 to 2000 m and from 1 to 10 min. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm characteristics and hydrodynamic model properties: rainfall sampling number (rainfall resolution vs. storm size), catchment sampling number (rainfall resolution vs. catchment size), runoff and sewer sampling number (rainfall resolution vs. runoff and sewer model resolution respectively). Results show that for rainfall resolution lower than half the catchment size, rainfall volumes mean and standard deviations decrease as a result of smoothing of rainfall gradients. Moreover, deviations in maximum water depths, from 10 to 30% depending on the storm, occurred for rainfall resolution close to storm size, as a result of rainfall aggregation. Model results also showed that modelled runoff peaks are more sensitive to rainfall resolution than maximum in-sewer water depths as flow routing has a damping effect on in-sewer water level variations. Temporal resolution aggregation of rainfall inputs led to increase in de-correlation lengths and resulted in time shift in modelled flow peaks by several minutes. Sensitivity to temporal resolution of rainfall inputs was low compared to spatial resolution, for the storms analysed in this study.
Yucel, I.; Onen, A.; Yilmaz, K. K.; Gochis, D. J.
A fully-distributed, multi-physics, multi-scale hydrologic and hydraulic modeling system, WRF-Hydro, is used to assess the potential for skillful flood forecasting based on precipitation inputs derived from the Weather Research and Forecasting (WRF) model and the EUMETSAT Multi-sensor Precipitation Estimates (MPEs). Similar to past studies it was found that WRF model precipitation forecast errors related to model initial conditions are reduced when the three dimensional atmospheric data assimilation (3DVAR) scheme in the WRF model simulations is used. A comparative evaluation of the impact of MPE versus WRF precipitation estimates, both with and without data assimilation, in driving WRF-Hydro simulated streamflow is then made. The ten rainfall-runoff events that occurred in the Black Sea Region were used for testing and evaluation. With the availability of streamflow data across rainfall-runoff events, the calibration is only performed on the Bartin sub-basin using two events and the calibrated parameters are then transferred to other neighboring three ungauged sub-basins in the study area. The rest of the events from all sub-basins are then used to evaluate the performance of the WRF-Hydro system with the calibrated parameters. Following model calibration, the WRF-Hydro system was capable of skillfully reproducing observed flood hydrographs in terms of the volume of the runoff produced and the overall shape of the hydrograph. Streamflow simulation skill was significantly improved for those WRF model simulations where storm precipitation was accurately depicted with respect to timing, location and amount. Accurate streamflow simulations were more evident in WRF model simulations where the 3DVAR scheme was used compared to when it was not used. Because of substantial dry bias feature of MPE, as compared with surface rain gauges, streamflow derived using this precipitation product is in general very poor. Overall, root mean squared errors for runoff were reduced by 22.2% when hydrological model calibration is performed with WRF precipitation. Errors were reduced by 36.9% (above uncalibrated model performance) when both WRF model data assimilation and hydrological model calibration was utilized. Our results also indicated that when assimilated precipitation and model calibration is performed jointly, the calibrated parameters at the gauged sites could be transferred to ungauged neighboring basins where WRF-Hydro reduced mean root mean squared error from 8.31 m3/s to 6.51 m3/s.
Pineda, Nicolau; Bech, Joan; Rigo, Tomeu; Montanyà, Joan
On the night from 1st to 2nd of November 2008, a multi-cell storm coming from the Mediterranean produced severe weather in the coastal area of Catalonia (NE Spain): ground-level strong damaging wind gusts, a tornado - which caused F2 damage - and heavy rainfall. A general overview of the synoptic framework, damage observed and a radar analysis is given in the first part of the study. This second part is mostly centered on the detailed analysis of the total lightning behavior, its relationship with radar-derived storm parameters, and total lightning correlation with hazardous weather. The purpose is to bring more evidence about the outstanding role of total lightning in severe weather surveillance tasks. The analysis of the storm cells life cycle has showed similar trends between the total lighting flash rates and radar-derived parameters like the area of reflectivity above 30 dBZ at 7-km. Regarding lightning trends, a lightning "jump" pattern - an abrupt increase of the total lightning rate in a short period of time - has been related to severe weather. On the contrary, cloud-to-ground lightning data did not show any pattern related to severe weather. In comparison to other parameters, like the IC:CG ratio, the lightning "jump" pattern seems more robust to forecast in a short-term basis the possible occurrence of severe weather.
Bracalente, Emedio M.
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.
and Computer Engineering, and the Atmospheric Radar Research Center, Univer- sity of Oklahoma, Norman, OK 73072 Center, University of Oklahoma, Norman, OK 73072 USA. D. Staiman is with Lockheed Martin Corporation and the School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73072 USA, and also
Souvignet, Maxime; Freer, Jim E.; de Almeida, Gustavo A. M.; Coxon, Gemma; Neal, Jeffrey C.; Champion, Adrian J.; Cloke, Hannah L.; Bates, Paul D.
Observed and numerical weather prediction (NWP) simulated precipitation products typically show differences in their spatial and temporal distribution. These differences can considerably influence the ability to predict hydrological responses. For flood inundation impact studies, as in forecast situations, an atmospheric-hydrologic-hydraulic model chain is needed to quantify the extent of flood risk. Uncertainties cascaded through the model chain are seldom explored, and more importantly, how potential input uncertainties propagate through this cascade, and how best to approach this, is still poorly understood. This requires a combination of modelling capabilities, the non-linear transformation of rainfall to river flow using rainfall-runoff models, and finally the hydraulic flood wave propagation based on the runoff predictions. Improving the characterisation of uncertainty, and what is important to include, in each component is important for quantifying impacts and understanding flood risk for different return periods. In this paper, we propose to address this issue by i) exploring the effects of errors in rainfall on inundation predictive capacity within an uncertainty framework by testing inundation uncertainty against different comparable meteorological conditions (i.e. using different rainfall products) and ii) testing different techniques to cascade uncertainties (e.g. bootstrapping, PPU envelope) within the GLUE (generalised likelihood uncertainty estimation) framework. Our method cascades rainfall uncertainties into multiple rainfall-runoff model structures using the Framework for Understanding Structural Errors (FUSE). The resultant prediction uncertainties in upstream discharge provide uncertain boundary conditions that are cascaded into a simplified shallow water hydraulic model (LISFLOOD-FP). Rainfall data captured by three different measurement techniques - rain gauges, gridded radar data and numerical weather predictions (NWP) models are evaluated. The study is performed in the Severn catchment over summer 2007, where a series of large rainfall events (over 100mm between the 20th and 21rst of July in certain sub-catchments) caused record floods in the study area. Differences in water level at benchmark stations are compared and the resulting prediction uncertainties are analysed for the different rainfall products. These results quantify how different cascading techniques and rainfall input uncertainty affects the resultant set of behavioural simulations. This allows us to compare the performance of different rainfall products used for real forecasting situations.
This Topic in Depth discusses the variety of instruments used to collect climate and weather data. The first two websites provide simple introductions to the many weather instruments. Bethune Academy's Weather Center (1) discusses the functions of psychrometers, anemometers, weather balloons, thermometers, and barometers. The Illinois State Water Survey (2) furnishes many images of various instruments that collect data daily for legal issues, farmers, educators, students, and researchers. The third website (3), created by the Center for Improving Engineering and Science Education (CIESE), provides a classroom activity to educate users on how to build and use weather instruments. By the end of the group project, students should know all about wind vanes, rain gauges, anemometers, and thermometers. Next, the Miami Museum of Science provides a variety of activities to help students learn about the many weather instruments including wind scales and wind chimes (4). Students can learn about the wind, air pressure, moisture, and temperature. At the fifth website, the Tyson Research Center at Washington University describes the devices it uses in its research (5). At the various links, users can find out the center's many projects that utilize meteorological data such as acid rain monitoring. The sixth website, a pdf document created by Dr. John Guyton at the Mississippi State University Extension Service, provides guidance to teachers about the education of weather patterns and instruments (6). Users can find helpful information on pressure systems, humidity, cloud patterns, and much more. Next, the University of Richmond discusses the tools meteorologists use to learn about the weather (7). While providing materials about the basic tools discussed in the other websites, this site also offers information about weather satellites, radar, and computer models. After discovering the many weather instruments, users can learn about weather data output and analysis at the Next Generation Weather Lab website (8). This expansive website provides an abundance of surface data and upper air data as well as satellite and radar images for the United States.
This 5-lesson unit gives students practice in using calculating, graphing and modeling skills to analyze varoius aspects of weather. Students calculate fractions of a set of rainfall data, graph damage costs of selected hurricanes, and make Venn diagrams to compare droughts and hurricanes. Visuals and student handouts are provided.
Zohidov, Bahtiyor; Andrieu, Hervé; Servières, Myriam; Normand, Nicolas
Rainfall is usually measured by networks of rain gauges and weather radars. Many cities worldwide are not supplied with these devices; however, they are generally equipped with mobile telecommunication networks. Mobile networks use atmospheric Hyper-Frequency (HF) links whose transmitted signal power is attenuated by rainfall. Measuring that signal attenuation along each link could allow the measurement of path-averaged rainfall [Leijnse et al 2007, Overeem et al 2013, Messer et al 2006, Guili et al 1991, Zinevich et al 2008, Cuccoli et al 2011]. As HF links are concentrated in cities, these networks could constitute a self-sufficient approach to monitoring rainfall in urban areas. We adopt a simulation approach in order to study the feasibility of mapping rainfall fields at the city scale by means of existing HF links. Our domain of study is the central part of the city of Nantes, France, where the density of cellular networks is greatest. As a basis, we use a data set consisting of hundreds of weather radar images recorded by the Météo-France C band weather radar at high spatial (250m x 250m) and temporal (5 minute) resolutions located about 10 km north of the center of Nantes. We convert these images into rainfall maps using the Z-R relation and consider them as reference rainfall fields. The simulation is performed as follows. First, we simulate the measurement of total attenuation along each HF link using a rain-attenuation model based on Mie theory and a known drop size distribution in a continental temperate climate. This procedure is applied for 256 real radio links operating at different frequencies (18, 23, 38 GHz) with lengths ranging from 0.4 to 16 km. This helps us to substitute the attenuation data for the signal power received from microwave links. Error sources affecting measurement accuracy are introduced as a zero-mean Gaussian distributed random variable with variance of 10% of total attenuation. The retrieval of the rainfield is performed by a nonlinear algorithm [Tarantola and Valette 1982] based on the general nonlinear least square criterion. The a priori knowledge used to initialize the algorithm heavily influences the model outcome if the stated problem is underdetermined. In order to evaluate the performance of our model, we carry out a series of rainfall retrieval tests for various rain events (convective and stratiform) with different time intervals. We evaluate retrieval efficiency by comparing observed rain fields with retrieved ones. We perform a sensitivity analysis to define the model's limitations and capabilities by considering essential factors, namely spatial and temporal rainfall structure, the geometry of HF link networks, the choice of a priori information and associated errors.
Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas
Machine learning (ML) algorithms have been successfully evaluated as valuable tools in satellite-based rainfall retrievals which shows the high potential of ML algorithms when faced with high dimensional and complex data. Moreover, the recent developments in parallel computing with ML offer new possibilities in terms of training and predicting speed and therefore makes their usage in real time systems feasible. The present study compares four ML algorithms for rainfall area detection and rainfall rate assignment during daytime, night-time and twilight using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path are applied as predictor variables. As machine learning algorithms, random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) are chosen. The comparison is realised in three steps. First, an extensive tuning study is carried out to customise each of the models. Secondly, the models are trained using the optimum values of model parameters found in the tuning study. Finally, the trained models are used to detect rainfall areas and to assign rainfall rates using an independent validation datasets which is compared against ground-based radar data. To train and validate the models, the radar-based RADOLAN RW product from the German Weather Service (DWD) is used which provides area-wide gauge-adjusted hourly precipitation information. Though the differences in the performance of the algorithms were rather small, NNET and AVNNET have been identified as the most suitable algorithms. On average, they showed the best performance in rainfall area delineation as well as in rainfall rate assignment. The fast computation time of NNET allows to work with large datasets as it is required in remote sensing based rainfall retrievals. However, since none of the algorithms performed considerably better that the others we conclude that research effort is needed in providing suitable predictors for rainfall rather than in optimizing by the choice of the ML algorithm.
Mead, Reginald; Paxton, John; Sojda, Richard S.
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.
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
A real time 24/7 automatic alert system is in operational use at the Finnish Meteorological Institute (FMI). It consists of gridded forecasts of the exceedance probabilities of rainfall class thresholds in the continuous lead time range of 1 hour to 5 days. Nowcasting up to six hours applies ensemble member extrapolations of weather radar measurements. With 2.8 GHz processors using 8 threads it takes about 20 seconds to generate 51 radar based ensemble members in a grid of 760 x 1226 points. Nowcasting exploits also lightning density and satellite based pseudo rainfall estimates. The latter ones utilize convective rain rate (CRR) estimate from Meteosat Second Generation. The extrapolation technique applies atmospheric motion vectors (AMV) originally developed for upper wind estimation with satellite images. Exceedance probabilities of four rainfall accumulation categories are computed for the future 1 h and 6 h periods and they are updated every 15 minutes. For longer forecasts exceedance probabilities are calculated for future 6 and 24 h periods during the next 4 days. From approximately 1 hour to 2 days Poor man's Ensemble Prediction System (PEPS) is used applying e.g. the high resolution short range Numerical Weather Prediction models HIRLAM and AROME. The longest forecasts apply EPS data from the European Centre for Medium Range Weather Forecasts (ECMWF). The blending of the ensemble sets from the various forecast sources is performed applying mixing of accumulations with equal exceedance probabilities. The blending system contains a real time adaptive estimator of the predictability of radar based extrapolations. The uncompressed output data are written to file for each member, having total size of 10 GB. Ensemble data from other sources (satellite, lightning, NWP) are converted to the same geometry as the radar data and blended as was explained above. A verification system utilizing telemetering rain gauges has been established. Alert dissemination e.g. for citizens and professional end users applies SMS messages and, in near future, smartphone maps. The present interactive user interface facilitates free selection of alert sites and two warning thresholds (any rain, heavy rain) at any location in Finland. The pilot service was tested by 1000-3000 users during summers 2010 and 2012. As an example of dedicated end-user services gridded exceedance scenarios (of probabilities 5 %, 50 % and 90 %) of hourly rainfall accumulations for the next 3 hours have been utilized as an online input data for the influent model at the Greater Helsinki Wastewater Treatment Plant.
Kummerow, C.; Simpson, J.; Thiele, O.; Barnes, W.; Chang, A. T. C.; Stocker, E.; Adler, R. F.; Hou, A.; Kakar, R.; Wentz, F.
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.
Wedan, R. W.
The implementation of the National Airspace System (NAS) will improve safety services to aviation. These services include collision avoidance, improved landing systems and better weather data acquisition and dissemination. The program to improve the quality of weather information includes the following: Radar Remote Weather Display System; Flight Service Automation System; Automatic Weather Observation System; Center Weather Processor, and Next Generation Weather Radar Development.
Bruni, G.; Reinoso, R.; van de Giesen, N. C.; Clemens, F. H. L. R.; ten Veldhuis, J. A. E.
Cities are increasingly vulnerable to floods generated by intense rainfall, because of their high degree of imperviousness, implementation of infrastructures, and changes in precipitation patterns due to climate change. 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 this paper, a detailed study of the sensitivity of urban hydrological response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar for four rainstorms were used as input into a detailed hydrodynamic sewer model for an urban catchment in Rotterdam, the Netherlands. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm 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 catchment smearing effect for rainfall resolution approaching half the catchment size, i.e. for catchments sampling numbers greater than 0.5 averaged rainfall volumes decrease about 20%. Moreover, deviations in maximum water depths, form 10 to 30% depending on the storm, occur for rainfall resolution close to storm size, describing storm smearing effect due to rainfall coarsening. Model results also show the sensitivity of modelled runoff peaks and maximum water depths to the resolution of the runoff areas and sewer density respectively. Sensitivity to temporal resolution of rainfall input seems low compared to spatial resolution, for the storms analysed in this study. Findings are in agreement with previous studies on natural catchments, thus the sampling numbers seem to be promising as an approach to describe sensitivity of hydrological response to rainfall variability for intra-urban catchments and local convective storms. More storms and different urban catchments of varying characteristics need to be analysed in order to validate these findings.
Collis, Scott; Tao, Wei-Kuo; Giangrande, Scott; Fridlind, Ann; Theisen, Adam; Jensen, Michael
Precipitation processes play a significant role in the energy balance of convective systems for example, through latent heating and evaporative cooling. Heavy precipitation "cores" can also be a proxy for vigorous convection and vertical motions. However, comparisons between rainfall rate retrievals from volumetric remote sensors with forecast rain fields from high-resolution numerical weather prediction simulations are complicated by differences in the location and timing of storm morphological features. This presentation will outline a series of metrics for diagnosing the spatial variability and statistical properties of precipitation maps produced both from models and retrievals. We include existing metrics such as Contoured by Frequency Altitude Diagrams (Yuter and Houze 1995) and Statistical Coverage Products (May and Lane 2009) and propose new metrics based on morphology, cell and feature based statistics. Work presented focuses on observations from the ARM Southern Great Plains radar network consisting of three agile X-Band radar systems with a very dense coverage pattern and a C Band system providing site wide coverage. By combining multiple sensors resolutions of 250m2 can be achieved, allowing improved characterization of fine-scale features. Analyses compare data collected during the Midlattitude Continental Convective Clouds Experiment (MC3E) with simulations of observed systems using the NASA Unified Weather Research and Forecasting model. May, P. T., and T. P. Lane, 2009: A method for using weather radar data to test cloud resolving models. Meteorological Applications, 16, 425-425, doi:10.1002/met.150, 10.1002/met.150. Yuter, S. E., and R. A. Houze, 1995: Three-Dimensional Kinematic and Microphysical Evolution of Florida Cumulonimbus. Part II: Frequency Distributions of Vertical Velocity, Reflectivity, and Differential Reflectivity. Mon. Wea. Rev., 123, 1941-1963, doi:10.1175/1520-0493(1995)123<1941:TDKAME>2.0.CO;2.
Kalmykov, A. I.; Velichko, S. A.; Tsymbal, V. N.; Kuleshov, Yu. A.; Weinman, J. A.; Jurkevich, I.
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.
Schuster, S. S.; Blong, R. J.; Leigh, R. J.; McAneney, K. J.
Hailstorms occur frequently in metropolitan Sydney, in the eastern Australian State of New South Wales, which is especially vulnerable due to its building exposure and geographical location. Hailstorms challenge disaster response agencies and pose a great risk for insurance companies. This study focuses on the Sydney hailstorm of 14 April 1999 - Australia's most expensive insured natural disaster, with supporting information from two other storms. Comparisons are drawn between observed hailstone sizes, radar-derived reflectivity and damage data in the form of insurance claims and emergency calls. The "emergency response intensity" (defined by the number of emergency calls as a proportion of the total number of dwellings in a Census Collection District) is a useful new measure of the storm intensity or severity experienced. The area defined by a radar reflectivity ?55 dBZ appears to be a good approximation of the damage swath on ground. A preferred area for hail damage is located to the left side of storm paths and corresponds well with larger hailstone sizes. Merging hail cells appear to cause a substantially higher emergency response intensity, which also corresponds well to maximum hailstone sizes. A damage threshold could be identified for hailstone sizes around 2.5 cm (1 cm), based on the emergency response intensity (insurance claims). Emergency response intensity and claims costs both correlate positively with hailstone sizes. Higher claim costs also occurred in areas that experienced higher emergency response intensities.
Dworak, Richard; Bedka, Kristopher; Brunner, Jason; Feltz, Wayne
Studies have found that convective storms with overshooting-top (OT) signatures in weather satellite imagery are often associated with hazardous weather, such as heavy rainfall, tornadoes, damaging winds, and large hail. An objective satellite-based OT detection product has been developed using 11-micrometer infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager. In this study, this method is applied to GOES-12 IRW data and the OT detections are compared with radar data, severe storm reports, and severe weather warnings over the eastern United States. The goals of this study are to 1) improve forecaster understanding of satellite OT signatures relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) evaluate the utility of an OT detection product for diagnosing hazardous convective storms. The coevolution of radar-derived products and satellite OT signatures indicates that an OT often corresponds with the highest radar echo top and reflectivity maximum aloft. Validation of OT detections relative to composite reflectivity indicates an algorithm false-alarm ratio of 16%, with OTs within the coldest IRW BT range (less than 200 K) being the most accurate. A significant IRW BT minimum typically present with an OT is more often associated with heavy precipitation than a region with a spatially uniform BT. Severe weather was often associated with OT detections during the warm season (April September) and over the southern United States. The severe weather to OT relationship increased by 15% when GOES operated in rapid-scan mode, showing the importance of high temporal resolution for observing and detecting rapidly evolving cloud-top features. Comparison of the earliest OT detection associated with a severe weather report showed that 75% of the cases occur before severe weather and that 42% of collocated severe weather reports had either an OT detected before a severe weather warning or no warning issued at all. The relationships between satellite OT signatures, severe weather, and heavy rainfall shown in this paper suggest that 1) when an OT is detected, the particular storm is likely producing heavy rainfall and/or possibly severe weather; 2) an objective OT detection product can be used to increase situational awareness and forecaster confidence that a given storm is severe; and 3) this product may be particularly useful in regions with insufficient radar coverage.
Hoedjes, Joost; Said, Mohammed; Becht, Robert; Kifugo, Shem; Kooiman, André; Limo, Agnes; Maathuis, Ben; Moore, Ian; Mumo, Mark; Nduhiu Mathenge, Joseph; Su, Bob; Wright, Iain
The existing meteorological infrastructure in Kenya is poorly suited for the countrywide real-time monitoring of precipitation. Rainfall radar is not available, and the existing network of rain gauges is sparse and challenging to maintain. This severely restricts Kenya's capacity to warn for, and respond to, weather related emergencies. Furthermore, the lack of accurate rainfall observations severely limits Kenya's climate change adaptation capabilities. Over the past decade, the mobile telephone network in Kenya has expanded rapidly. This network makes extensive use of terrestrial microwave (MW) links, received signal level (RSL) data from which can be used for the calculation of rainfall intensities. We present a novel method for the near-real time observation of convective rainfall over Kenya, based on the combined use of MW RSL data and Meteosat Second Generation (MSG) satellite data. In this study, the variable density rainfall information derived from several MW links is scaled up using MSG data to provide full rainfall information coverage for the region surrounding the links. Combining MSG data and MW link derived rainfall data for several adjacent MW links makes it possible to make the distinction between wet and dry pixels. This allows the disaggregation of the MW link derived rainfall intensities. With the distinction between wet and dry pixels made, and the MW derived rainfall intensities disaggregated, these data can then be used to develop instantaneous empirical relationships linking rainfall intensities to cloud physical properties. These relationships are then used to calculate rainfall intensities for the MSG scene. Since both the MSG and the MW data are available at the same temporal resolution, unique empirical coefficients can be determined for each interval. This approach ensures that changes in convective conditions from one interval to the next are taken into account. Initial results from a pilot study, which took place from November 2012 until January 2013, are presented. The work has been carried out in close cooperation with mobile telephone operator Safaricom, using RSL data from 15 microwave links in rain prone areas in Western Kenya (out of a total of 3000 MW links operated by Safaricom in Kenya). The data supplied by Safaricom consist of the mean, minimum and maximum RSL for each MW link over a 15 minute interval. For this pilot study, use has been made of the MSG Cloud Top Temperature data product from the Royal Dutch Meteorological Institute's MSG Cloud Physical Properties database (http://msgcpp.knmi.nl/).
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.
This resource provides an overview of weather, the day-to-day changes in temperature, air pressure, moisture, wind, cloudiness, rainfall and sunshine. Links embedded in the text provide access to descriptions of cloud types and to information on weather hazards such as fog, hurricanes, thunderstorms, and tornadoes. Other topics include meteorology, weather measurements, and weather mapping. Materials are also provided on the water cycle and its elements, such as evaporation, uplift and cooling of air, dew point, condensation, and precipitation.
Chapter 7 Conclusion Extratropical cyclones are fundamental to the everyday weather that these cyclones are predicted as accurately and as far in advance as possible by numerical weather prediction (NWP) models. The aim of this thesis is to explore the prediction of extratropical cyclones by NWP using
This site offers links to a variety of weather information, including national, international and local weather maps and forecasts, satellite and radar imagery, and severe weather warnings. There are also links to diverse resources such as fire maps, glacier inventories, snow depths, storm surges and tropical storms. There are reports and advisories about El Nino and La Nina. The site also has a glossary of weather terms and conversion charts for temperature, wind speed and atmospheric pressure.
Rusjan, S.; Kobold, M.; Mikoš, M.
During a weather front that passed over large parts of Slovenia on 18.9.2007, extreme rainfall events were triggered causing several severe flash floods with six casualties. Out of 210 municipalities in Slovenia, 60 were reporting flood damages, and the total economic flood damage was later estimated at close to 200 million Euro; highest damage was claimed by Železniki municipality in NW Slovenia. The main purpose of the study presented in this paper was to put together available meteorological and hydrological data in order to get better insight into temporal and spatial dynamics and variability of the flash flood event along the Sel\\vska Sora River flowing through the town of Železniki. The weather forecast by the Environmental Agency of the Republic of Slovenia (ARSO) lead to early warning of floodings but has underestimated rainfall amounts by a factor of 2. Also meteorological radar underestimated ground rainfall as much as by 50%. During that day, in many rainfall gauging stations operated by ARSO in the area under investigation, extreme rainfall amounts were measured, e.g. 303 mm in 24 h or 157 mm in 2 h. Some of the measured rainfall amounts were the highest registered amounts in Slovenia so far. Statistical analysis using Gumble distribution was performed and rainfall return periods were estimated. When assessing rainfall return periods, a question of the sampling error as a consequence of short rainfall records used was raised. Furthermore, measured rainfall data were used to reconstruct hydrographs on selected water stations along the Sel\\vska Sora River. The cumulative areal precipitation for the Sel\\vska Sora River catchment upstream of Železniki amounted to 219 mm, while the modeled effective precipitation used to simulate the hydrograph peak was only 57 mm. The modeled direct runoff coefficient therefore amounts to 0.26. Surprisingly low value is mainly caused by the applied unit hydrograph method that seeks to meet the peak discharge rather than hydrograph volume. However, the spatial distribution of the rainfall in the area was highly variable and present spatial positioning of rain gauges is obviously inadequate for proper representation of the actual spatial amount of rainfall. The study confirmed that post-flood investigation should focus on discharges and hydrological response of the catchment rather than simply analyzing statistical characteristics of rainfall.
on the Internet for incorporation into nowcasting, hydrology and modeling applications in near-realtime. Radar by the National Weather Service are the Weather Surveillance Radar 1998 Doppler (WSR-88D). There are 142 attenuation properties, and are capable of a surveillance (radar reflectivity-range only) of 920km
Damage Survey, Radar, and Environment Analyses on the First-Ever Documented Tornado in Beijing the most detailed information in all of the published tornado damage surveys so far in China, this work showed significant evidence that the wind damage was caused by a mesocyclonic tornado rated as a category
Reading, University of
and sorting them into snow and graupel categories using the value of the Linear Depolarization Ratio the whole region scanned by radar leads to only marginal improvement in rain estimates. Instead, this work implications for iceparametrization schemes in mesoscale models. KEYWORDS:Linear Depolarization Ratio
The Unisys weather website offers a host of weather analyses and forecasts. In the Analyses link, visitors can find satellite images as well as surface, upper air, and radar images. Visitors can learn the intricacies of Unisys's many forecast models such as the Nested Grid Model (NGM), Aviation Model, and the Rapid Update Cycle (RUC) Model. Users can find archived hurricane data for the Atlantic, the Eastern Pacific, and the Western Pacific. The site also furnishes archived surface maps, infrared satellite images, upper air charts, and sea surface temperature (SST) plots.
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.
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 of Engineers Hydrologic Engineering Center hydrologic and hydraulic modelling chain. The characteristics of this tool make it ideal to support flood monitoring and forecasting within urban environment and small-scale basins. Preliminary results, carried out during a field campaign in Moldova, showed that the mini-radar based hydro-meteorological forecasting system can constitute a suitable solution for local flood warning and civil flood protection applications.
Wright, Daniel; Yatheendradas, Soni; Peters-Lidard, Christa; Kirschbaum, Dalia; Ayalew, Tibebu; Mantilla, Ricardo; Krajewski, Witold
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.
Buechler, D. E.; McCaul, E. W., Jr.; Goodman, S. J.; Blakeslee, R. J.; Bailey, J. C.; Gatlin, P.
On the afternoon and evening of 10 November 2002, the Midwest and Deep South were struck by a major outbreak of severe storms that produced some 80 tornadoes. In terms of number of tornadoes, this was the largest outbreak in the United States since November 1992. Some 32 of the tornadoes occurred in Tennessee, Mississippi, Alabama and Georgia, including several long-track killers. We use the North Alabama Lightning Mapping Array (LMA) and other data sources to perform a comprehensive analysis of the structure and evolution of the outbreak. Most of the Southern tornadoes occurred in isolated, fast-moving supercell storms that formed in warm, moist air ahead of a major cold front. Storms tended to form in lines parallel to storm cell motion, resulting in many communities being hit multiple times by severe storms that evening. Supercells in Tennessee produced numerous strong tornadoes with short to medium-length track paths, while the supercells further south produced several very long-track tornadoes. Radar data indicate that the Tennessee storms tended to split frequently, apparently limiting their ability to sustain long-lived tornadoes, while storms further south split at most one time. The differences between these storms appear to be related to the presence of stronger jetstream winds in Tennessee relative to those present in Mississippi, Alabama and Georgia. LMA-derived flash rates associated with most of the supercell storm cores were about 1-2 flashes per second. Rapid increases in lightning rates (or "jumps") occurred prior to tornado touchdown in many instances. Lightning "holes" (lightning-free regions associated with the echo-free vault) occurred in two of the Tennessee supercells. The complexity of the relationship between lightning and storm severity is revealed by the behavior of one Alabama supercell, which produced a peak flash rate of nearly 14 flashes per second, well after the end of its long-track tornado, while interacting and ultimately merging with a daughter supercell on its southwest flank. Close examination of this powerful storm indicates that its prodigious flash rate was the result of strong flash activity over an unusually large area, rather than a concentrated core of extremely high flash rate activity.
Gabriel, Philip M.; Yeh, Penshu; Tsay, Si-Chee
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.
Takayabu, Yukari; Hamada, Atsushi; Mori, Yuki; Murayama, Yuki; Liu, Chuntao; Zipser, Edward
While extreme rainfall has a huge impact upon human society, the characteristics of the extreme precipitation vary from region to region. Seventeen years of three dimensional precipitation measurements from the space-borne precipitation radar equipped with the Tropical Precipitation Measurement Mission satellite enabled us to describe the characteristics of regional extreme precipitation globally. Extreme rainfall statistics are based on rainfall events defined as a set of contiguous PR rainy pixels. Regional extreme rainfall events are defined as those in which maximum near-surface rainfall rates are higher than the corresponding 99.9th percentile in each 2.5degree x2.5degree horizontal resolution grid. First, regional extreme rainfall is characterized in terms of its intensity and event size. Regions of ''intense and extensive'' extreme rainfall are found mainly over oceans near coastal areas and are likely associated with tropical cyclones and convective systems associated with the establishment of monsoons. Regions of ''intense but less extensive'' extreme rainfall are distributed widely over land and maritime continents, probably related to afternoon showers and mesoscale convective systems. Regions of ''extensive but less intense'' extreme rainfall are found almost exclusively over oceans, likely associated with well-organized mesoscale convective systems and extratropical cyclones. Secondly, regional extremes in terms of surface rainfall intensity and those in terms of convection height are compared. Conventionally, extremely tall convection is considered to contribute the largest to the intense rainfall. Comparing probability density functions (PDFs) of 99th percentiles in terms of the near surface rainfall intensity in each regional grid and those in terms of the 40dBZ echo top heights, it is found that heaviest precipitation in the region is not associated with tallest systems, but rather with systems with moderate heights. Interestingly, this separation of extremely heavy precipitation from extremely tall convection is found to be quite universal, irrespective of regions. Rainfall characteristics and environmental conditions both indicate the importance of warm-rain processes in producing extreme rainfall rates. Thus it is demonstrated that, even in regions where severe convective storms are representative extreme weather events, the heaviest rainfall events are mostly associated with less intense convection. Third, the size effect of rainfall events on the precipitation intensity is investigated. Comparisons of normalized PDFs of foot-print size rainfall intensity for different sizes of rainfall events show that footprint-scale extreme rainfall becomes stronger as the rainfall events get larger. At the same time, stratiform ratio in area as well as in rainfall amount increases with the size, confirming larger sized features are more organized systems. After all, it is statistically shown that organization of precipitation not only brings about an increase in extreme volumetric rainfall but also an increase in probability of the satellite footprint scale extreme rainfall.
Quantitative precipitation estimation and forecasting continue to be critical components of the weather research programs. The objective of this dissertation is twofold: First, to propose a method that fuses rainfall measurements from rain gages and radar. Second, to design a technique that produces real-time rainfall forecasts for the next hour. Cokriging is perhaps the most widely used method to fuse measurements from two sensors, for example, radar and rain gages. Here an alternative fusion methodology, based on recent developments in Artificial Neural Networks (ANNs) is presented. ANNs are nonlinear estimators and thus have a distinct advantage over traditional statistical methods. Intercomparison of rainfall estimation, using cokriging and ANN methods, suggests that ANNs provide a more attractive and robust fusion from radar and rain gages for several storms from Oklahoma. It is shown that simply nowcasting the fused estimates gives better forecasts than the traditional nowcasting with radar data. Moreover, the rainfall field at the next hour is predicted with a methodology that is based on radial-basis ANNs. The advantage of this method is that it provides a framework for the automated segmentation of the rainfall field in rainfall clusters that have their own advection vectors. Each cluster is shifted individually for the prediction step. Thus, the method accounts for nonhomogeneous advection conditions. The results show that this method has the capability to generate improved predictions compared to nowcasting. It appears that its full strength will be realized if a data set with a temporal resolution finer than hourly is used. In summary, an integrated ANN approach has been produced that estimates rainfall from two sensors and produces a forecast. In the appendix I also include a study on the nature of long-range rainfall and streamflow correlations, using a method called Detrended Fluctuation Analysis. The findings show the existence of power-law correlations in both variables. Moreover, it is shown that what controls the correlation structure is not the actual rainfall values, but the pattern of alternating wet and dry spells. The employed method also highlights the dampening effect of the soil in the transformation of rainfall to streamflow.
Ochoa-Rodriguez, Susana; Wang, Li-Pen; Gires, Auguste; Pina, Rui; Reinoso-Rondinel, Ricardo; Bruni, Guendalina; Ichiba, Abdellah; Gaitan, Santiago; Cristiano, Elena; van Assel, Johan; Kroll, Stefan; Murlà-Tuyls, Damian; Schertzer, Daniel; Tchiguirinskaia, Ioulia; Willems, Patrick; Onof, Christian; ten Veldhuis, Marie-Claire
Urban hydrological applications require high resolution precipitation and catchment information in order to well represent the spatial variability, fast runoff processes and short response times of urban catchments. Although fast progress has been made over the last few decades in high resolution measurement of rainfall at urban scales, including increasing use of weather radars, the resolution of the currently available rainfall estimates (typically 1 x 1 km2 in space and 5 min in time) may still be too coarse to meet the stringent spatial-temporal scales characteristic of urban catchments. In addition, current evidence is still insufficient to provide a concrete answer regarding rainfall input resolution requirements of urban hydrological applications. With the aim of providing further evidence in this regard, in the framework of the EU Interreg RainGain project a collaborative study was conducted which investigated the impact of rainfall estimates for a range of spatial and temporal resolution combinations on the outputs of operational semi distributed models of seven urban catchments in North-West Europe. Nine storm events measured by a dual polarimetric X-band weather radar, located in the Cabauw Experimental Site for Atmospheric Research (CESAR) of the Netherlands, were selected for analysis. Based on the original radar estimates, at 100 m and 1 min resolutions, 15 different combinations of coarser spatial and temporal resolutions, up to 3000 m and 10 min, were generated. These estimates were applied to the hydraulic models of the urban catchments, all of which have similar size (between 3 and 8 km2), but different morphological, hydrological and hydraulic characteristics. When doing so, methodologies for standardising model outputs and making results comparable were implemented. Results were analysed in the light of storm and catchment characteristics. Three main features were observed in the results: (1) the impact of rainfall input resolution decreases as catchment drainage area increases; (2) in general, the variation in temporal resolution of rainfall inputs affects hydrodynamic model results more strongly than variations in spatial resolution; (3) there is a strong interaction between the spatial and temporal resolution of rainfall input estimates and in order to avoid losing relevant information from the rainfall fields, the two resolutions must be in agreement with each other. Based on these results, initial models to quantify the impact of rainfall input resolution as a function of catchment size and spatial-temporal characteristics of storms are proposed and discussed.
Troch, P. A.; Volkmann, T.; Lyon, S. W.; Gupta, H.
Despite the availability of weather radar data at high spatial (1 km^2) and temporal (5-15 min) resolution, ground-based rain gauges are still needed to accurately estimate storm rainfall input to catchments during flash flood events. This is especially true in mountainous catchments where estimating storm depth and intensity from radar data is more challenging than in flat terrain. Given economical limitations on the number of rain gauges, a long-standing problem in catchment hydrology is where to put the (limited amount of) rain gauges to best capture both storm rainfall depth and temporal variability of storm intensity during extreme events. This study addresses the question whether it is possible to predict the best locations for rain gauge installation given a basin's topography and dominant storm tracks. A network of 40 tipping bucket rain gauges was deployed in the Sabino Canyon catchment near Tucson, AZ, during the summer monsoon season of 2006. An extreme, multi-day rainfall event during 27-31 July 2006 caused record flooding and an unprecedented series of slope failures and debris flows in the Santa Catalina Mountains. Geostatistics (kriging with external drift, KED) was used to combine the tipping bucket rain gauge observations with NEXRAD weather radar to create rasterized rainfall maps with high spatial (1 km^2) and temporal (15 min) resolution over the entire multi-day rainfall event. We use these KED rainfall maps to determine the optimized locations for an installation of 1 up to 4 rain gauges considering all possible subsets of 1 to 4 grid cells over the entire rainfall event. Our optimization method minimizes both the residual percent bias and the coefficient of correlation between the mean areal rainfall obtained using the KED rainfall maps and mean rainfall determined using each subset. This method was applied to the entire record of rainfall observations to identify networks consisting of 1 to 4 rain gauges which represent the ‘best' compromise between the two criteria. To determine the effect of the length of record of observations on the selected rain gauge networks, ‘best' compromise networks were identified using the same method treating each single rainfall event (seven in total) independently. A semi-arid rainfall-runoff model (KINEROS2) was then used to evaluate each ‘best' compromise rain gauge network. The performance statistics for model runs from all ‘best' networks were evaluated against a calibrated simulation of KINEROS2 based on the full spatial extent of the KED rainfall map (representing an installation of 94 rain gauges). In addition, to test how each ‘best' gauge network compared with random rain gauge configurations, average performance statistics for an ensemble of 1,000 randomly selected subsets of 1 to 4 grid cells were determined.
Droegemeier, Kelvin K.
Sampling Strategies for Tornado and Mesocyclone Detection Using Dynamically Adaptive Doppler Radars-polarization Doppler weather radars to overcome the inability of widely spaced, high-power radars to sample large of a CASA radar in comparison to that of a Weather Surveillance Radar-1988 Doppler (WSR- 88D) at close range
Teschl, Reinhard; Süsser-Rechberger, Barbara; Paulitsch, Helmut
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.
Uijlenhoet, Remko; Overeem, Aart; Leijnse, Hidde; Rios Gaona, Manuel Felipe
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 and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. 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. This is particularly interesting for those countries where few surface rainfall observations are available. Here we present almost two years of country-wide rainfall maps employing cellular communication networks. A data set from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (~ 2000) covering the land surface of the Netherlands (35500 square kilometers). This data set almost completely covers the years 2011 and 2012. Fifteen-minute and daily rainfall maps (1 km spatial resolution) are derived from the microwave link data and compared to maps from a gauge-adjusted radar data set. The performance of the rainfall retrieval algorithm will be studied, particularly differences in time and space. Time series of air temperature and snow from automatic weather stations, operated by the Royal Netherlands Meteorological Institute, will be collocated with the link-based rainfall data, to systematically study the performance of the algorithm during the two-year period. Moreover, a case study will be presented to investigate the performance of the algorithm during snow and sleet or to show the influence of dew formation on the antennas on the received signal levels.
Tokay, Ali; Petersen, Walter Arthur; Gatlin, Patrick N.; Wingo, Matt; Wolff, David B.; Carey, Lawrence D.
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.
Tokay, Ali; Petersen, Arthur; Gatlin, Patrick N.; Wingo, Matt; Wolff, David B.; Carey, Lawrence D.
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.
Marécal, Virginie; Mahfouf, Jean-François; Bauer, Peter
The objectives of this paper are to perform a comparison between three rainfall-rate estimates from Tropical Rainfall Measuring Mission Microwave Imager (TMI) data and to study their impact in the European Centre for Medium-Range Weather Forecasts (ECMWF) four-dimensional variational (4D-Var) assimilation system. The three algorithms for rainfall estimation considered are: Precipitation Radar Adjusted TMI Estimation of Rainfall (PATER), Bayesian Algorithm for Microwave-based Precipitation Retrieval (BAMPR-P), and the National Aeronautics and Space Administration operational algorithm 2A12 level 5. Results from the comparison show that BAMPR-P and 2A12 retrievals provide on average higher rain rates by about a factor of 1.5 with respect to PATER, mainly because of the different spatial resolutions and rain detection methods used in the three algorithms. The three TMI products are then compared to the rainfall rates from the ECMWF model. Globally, the rain occurrence simulated by the ECMWF model is higher than in TMI estimates. The model also produces lower rainfall rates in precipitating systems. PATER retrievals are generally closer to the model than those from other algorithms. Three 15-day assimilation experiments ('Rain-PATER', 'Rain-BAMPR-P' and 'Rain-2A12') were run using the three TMI rainfall-rate estimates in the ECMWF 4D-Var assimilation system. Fairly small differences were found between the global analyses and forecasts from all experiments and a control experiment without rainfall-data assimilation. This is explained by the small number of TMI rain observations which are used per assimilation cycle compared to the other types of observational data. The local impact on analyses was studied in two cases, namely a tropical cyclone ('Bonnie') and a midlatitude front propagating into the subtropics. For these two cases, the differences between the three TMI products and their associated errors lead to significant changes in the humidity and wind analyses.
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…
Liguori, Sara; O'Loughlin, Fiachra; Souvignet, Maxime; Coxon, Gemma; Freer, Jim; Woods, Ross
This research presents a newly developed observed sub-daily gridded precipitation product for England and Wales. Importantly our analysis specifically allows a quantification of rainfall errors from grid to the catchment scale, useful for hydrological model simulation and the evaluation of prediction uncertainties. Our methodology involves the disaggregation of the current one kilometre daily gridded precipitation records available for the United Kingdom. The hourly product is created using information from: 1) 2000 tipping-bucket rain gauges; and 2) the United Kingdom Met-Office weather radar network. These two independent datasets provide rainfall estimates at temporal resolutions much smaller than the current daily gridded rainfall product; thus allowing the disaggregation of the daily rainfall records to an hourly timestep. Our analysis is conducted for the period 2004 to 2008, limited by the current availability of the datasets. We analyse the uncertainty components affecting the accuracy of this product. Specifically we explore how these uncertainties vary spatially, temporally and with climatic regimes. Preliminary results indicate scope for improvement of hydrological model performance by the utilisation of this new hourly gridded rainfall product. Such product will improve our ability to diagnose and identify structural errors in hydrological modelling by including the quantification of input errors. References  Keller V, Young AR, Morris D, Davies H (2006) Continuous Estimation of River Flows. Technical Report: Estimation of Precipitation Inputs. in Agency E (ed.). Environmental Agency.
Smith, Eric A.; Ou, Mi-Lim
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 diabatic heating during the early stages of a forecast period. This procedure is expected to enhance details in the moisture field during model integration, and thus improve spinup performance, assuming the errors in the future time latent heating data ate less than intrinsic model background errors.
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)
Poehler, H. A.
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.
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Hardegree, S. P.
The National Weather Service (NWS) operates approximately 160 WSR-88D radar-precipitation stations as part of a Next Generation Radar (NEXRAD) program that began implementation in 1992. Among other products, these radar sites provide spatial rainfall estimates, at approximately 4 km2 resolution (Stage 1, Level 3 data), with nominal coverage of 96% of the coterminous United States. Effective coverage is much less than this in a given radar domain depending upon storm type and topography. As the original intent of this network was to support operational objectives of the Departments of Defense, Transportation and Commerce, the production of these data have been optimized for detection and mitigation of severe weather events that might result in flooding, destruction of property and loss of life. The primary hydrologic application has been river and flood forecast modeling by 13 NWS River Forecast Centers (RFC). As each RFC is responsible for a large river drainage, data processing and quality control of these data are geared toward optimization over a relatively large spatial domain (>100,000 km2). Use of these data for other hydrologic and natural resource applications is hampered by a lack of tools for data access and manipulation. NWRC has modified decoding and geo-referencing programs to facilitate utilization of these data for other research and management applications. Stage 1, Level 3 Digital Precipitation Array (DPA) files were obtained for the Boise, Idaho radar location (CBX) for the period of January 1998 to December 2000. Nine rain-gauge locations in the Reynolds Creek Experimental Watershed and Snake River Birds of Prey National Conservation Area, south of Boise, were georeferenced relative to the CBX Hydrologic Rainfall Analysis Project (HRAP) grid. NEXRAD estimates of total cumulative rainfall at these sites averaged only 20% of that measured by the local gauge network. This underestimate was attributed in the most part to truncation of low intensity rainfall events by the precipitation detection function (pdf) rather than to mis-calibration of the ZR relationship. At this time, these data are unsuitable as inputs for long-term water balance modeling but may be useful in extreme-event or flood-modeling applications. New tools to extract and manipulate specific subsets of Stage 1, Level 2 radar data may improve our ability to use radar reflectance data for a broader number of applications than are currently supported.
Ma, Shujie; Rodó, Xavier; Song, Yongjia; Cash, Benjamin A.
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 present in the observed BoB 10-20-day ISOs. Further analysis indicates that the intraseasonal variability of the ISMR is generally underrepresented in the simulations. Skill of the MME in seasonal ISMR forecasting is strongly dependent on individual model performance. Therefore, in order to improve the model skill with respect to seasonal ISMR forecasting, we suggest it is necessary to better represent the robust dynamical links between the ISOs and the relevant circulation variations, as well as the proportion of intraseasonal variability in the individual models.
Marks, David A.; Wolff, David B.; Carey, Lawrence D.; Tokay, Ali
Weather radars, recording information about precipitation around the globe, will soon be significantly upgraded. Most of today s weather radars transmit and receive microwave energy with horizontal orientation only, but upgraded systems have the capability to send and receive both horizontally and vertically oriented waves. These enhanced "dual-polarimetric" (DP) radars peer into precipitation and provide information on the size, shape, phase (liquid / frozen), and concentration of the falling particles (termed hydrometeors). This information is valuable for improved rain rate estimates, and for providing data on the release and absorption of heat in the atmosphere from condensation and evaporation (phase changes). The heating profiles in the atmosphere influence global circulation, and are a vital component in studies of Earth s changing climate. However, to provide the most accurate interpretation of radar data, the radar must be properly calibrated and data must be quality controlled (cleaned) to remove non-precipitation artifacts; both of which are challenging tasks for today s weather radar. The DP capability maximizes performance of these procedures using properties of the observed precipitation. In a notable paper published in 2005, scientists from the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) at the University of Oklahoma developed a method to calibrate radars using statistically averaged DP measurements within light rain. An additional publication by one of the same scientists at the National Severe Storms Laboratory (NSSL) in Norman, Oklahoma introduced several techniques to perform quality control of radar data using DP measurements. Following their lead, the Topical Rainfall Measuring Mission (TRMM) Satellite Validation Office at NASA s Goddard Space Flight Center has fine-tuned these methods for specific application to the weather radar at Kwajalein Island in the Republic of the Marshall Islands, approximately 2100 miles southwest of Hawaii and 1400 miles east of Guam in the tropical North Pacific Ocean. This tropical oceanic location is important because the majority of rain, and therefore the majority of atmospheric heating, occurs in the tropics where limited ground-based radar data are available.
Thiele, Otto W.
Plans to obtain ground truth data for the validation of the Tropical Rainfall Measuring Mission (TRMM) are examined. The experimental rainfall measuring techniques considered for the program are discussed, including optical and Doppler rain gages, satellite beacon attenuation, underwater hydrophones, profilers, microwave attenuation, multiple frequency/polarization radar, and scanning and airborne Doppler radar. The TRMM validation program is considered, noting observations to compare averaged TRMM rainfall data with similar ground truth data and to compare the rainfall and height distribution data from TRMM with instantaneous ground truth data.
Krajewski, Witold F.; Rexroth, David T.; Kiriaki, Kiriakie
Two problems related to radar rainfall estimation are described. The first part is a description of a preliminary data analysis for the purpose of statistical estimation of rainfall from multiple (radar and raingage) sensors. Raingage, radar, and joint radar-raingage estimation is described, and some results are given. Statistical parameters of rainfall spatial dependence are calculated and discussed in the context of optimal estimation. Quality control of radar data is also described. The second part describes radar scattering by ellipsoidal raindrops. An analytical solution is derived for the Rayleigh scattering regime. Single and volume scattering are presented. Comparison calculations with the known results for spheres and oblate spheroids are shown.
The Plymouth State Weather Center provides a variety of weather information, including a tropical weather menu with current and archived data on tropical depressions, storms, or hurricanes in the Atlantic or Eastern Pacific Oceans. An interactive Weather Product Generator allows students to make their own surface data maps and meteograms (24-hour summaries of weather at a specific location), and view satellite imagery. There are also interactive weather maps for the U.S., Canada, and Alaska that display the latest observations, and text servers which provide current written observations for New England and North America. A set of past and current weather data products provides information on minimum and maximum temperatures, wind chill, and heat index. In addition, there are collections of satellite loops/movies, radar/lightning images, loops, and movies, and a set of tutorials on clouds, the sun and its effects on the environment, and balanced atmospheric flows.
Shepherd, J. Marshall
Urbanization is one of the extreme cases of land use change. Most of world's population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in d e near future. It is estimated that by the year 2025, 60% of the world's population will live in cities. Human activity in urban environments also alters weather and climate processes. However, our understanding of urbanization on the total Earth-weather-climate system is incomplete. Recent literature continues to provide evidence that anomalies in precipitation exist over and downwind of major cities. Current and future research efforts are actively seeking to verify these literature findings and understand potential cause-effect relationships. The novelty of this study is that it utilizes rainfall data from multiple satellite data sources (e.g. TRMM precipitation radar, TRMM-geosynchronous-rain gauge merged product, and SSM/I) and ground-based measurements to identify spatial anomalies and temporal trends in precipitation for cities around the world. We will also present results from experiments using a regional atmospheric-land surface modeling system. Early results will be presented and placed within the context of weather prediction, climate assessment, and societal applications.
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...
Anagnostou, Marios N.; Kalogiros, John; Marzano, Frank S.; Anagnostou, Emmanouil N.; Baldini, Luca; Nikolopoulos, EfThymios; Montopoli, Mario; Picciotti, Errico
The Mediterranean area concentrates the major natural risks related to the water cycle, including heavy precipitation and flash-flooding during the fall season. Every year in central and south Europe we witness several fatal and economical disasters from severe storm rainfall triggering Flash Floods, and its impacts are increasing worldwide, but remain very difficult to manage. The spatial scale of flash flood occurrence is such that its vulnerability is often focused on dispersed urbanization, transportation and tourism infrastructures (De Marchi and Scolobig 2012). Urbanized and industrialized areas shows peculiar hydrodynamic and meteo-oceanographic features and they concentrate the highest rates of flash floods and fatal disasters. The main causes of disturbance being littoral urban development and harbor activities, the building of littoral rail- and highways, and the presence of several polluted discharges. All the above mentioned characteristics limit our ability to issue timely flood warnings. Precipitation estimates based on raingauge networks are usually associated with low coverage density, particularly at high altitudes. On the other hand, operational weather radar networks may provide valuable information of precipitation at these regimes but reliability of their estimates is often limited due to retrieval (e.g. variability in the reflectivity-to-rainfall relationship) and spatial extent constrains (e.g. blockage issues, overshooting effects). As a result, we currently lack accurate precipitation estimates over urban complex terrain areas, which essentially means that we lack accurate knowledge of the triggering factor for a number of hazards like flash floods and debris flows/landslides occurring in those areas. A potential solution to overcome sampling as well as retrieval uncertainty limitations of current observational networks might be the use of network of low-power dual-polarization X-band radars as complement to raingauges and gap-filling to operational, low-frequency (C-band or S-ban) and high-power weather radars. The above hypothesis is examined using data collected during the HyMEX 2012 Special Observation Period (Nov-Feb) the urban and sub-urban complex terrain area in the Central Italy (CI). The area is densely populated and it includes the high-density populated urban and industrial area of Rome. The orography of CI is quite complex, going from sea level to nearly 3000 m in less than 150 km. The CI area involves many rivers, including two major basins: the Aniene-Tiber basin (1000 km long) and the Aterno-Pescara basin (300 km long), respectively on the west and on the east side of the Apennines ridge. Data include observations from i) the National Observatory of Athens' X-band polarimetric weather radar (XPOL), ii) two X-band miniradars (WR25X located in CNR, WR10X located in Rome Sapienza), iii) a dense network of raingauges and disdrometers (i.e. Parsivel type and 2D-video type). In addition, the experimental area is also covered from the nearby the National Research Council (CNR)'s C-band dual-polarization weather radar (Polar55C), which were involved also in the analysis. A number of storm events are selected and compared with the nearby C-band radar to investigate the potential of using high-resolution and microphysically-derived rainfall based on X-band polarimetric radar observations. Events have been discriminated on the basis of rainfall intensity and hydrological response. Results reveal that in contrast with the other two rainfall sources (in situ and C-band radar), X-band radar rainfall estimates offer an improved representation of the local precipitation variability, which turns to have a significant impact in simulating the peak flows associated with these events.
Yucel, Ismail; Onen, Alper; Yilmaz, Koray; Gochis, David
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 where WRF-Hydro reduced mean root mean squared error from 8.31 m3/s to 6.51 m3/s.
The National Aeronautics and Space Administration (NASA) and the National Space Development Agency (NASDA) of Japan have joined to create the Tropical Rainfall Measuring Mission (TRMM). The goal of this mission is to "monitor and study tropical rainfall and the associated release of energy that helps to power the global atmospheric circulation shaping both weather and climate around the globe." Sections included at the Website are Spacecraft, Background, Validation, Data, Image Archive, and related Links. An interesting feature of this site is the Background section entitled Why do we need TRMM. A brief, illustrated synopsis is provided for all ages, ranging from the elementary school level to the post graduate level.
A. M. Horne; G. Yates
Synthetic aperture radar (SAR) is becoming increasingly important in many military ground surveillance and targeting roles because of its ability to operate in all weather, day and night, and to detect, classify and geolocate objects at long stand-off ranges. Bistatic SAR, where the transmitter and receiver are on separate platforms, is seen as a potential means of countering vulnerability. This
This site features links to thirty-five NASA radar images of the world's volcanoes, including brief descriptions of the respective processes and settings involved. The images were created with the Spaceborne Imaging Radar-C and X-Band Synthetic Aperture Radar (SIR-C/X-SAR) as part of NASA's Mission to Planet Earth. The radar illuminates Earth with microwaves allowing detailed observations at any time, regardless of weather or sunlight conditions.
Wedan, R. W.
Requirements for an improved aviation weather system are defined and specifically include the need for (1) weather observations at all airports with instrument approaches, (2) more accurate and timely radar detection of weather elements hazardous to aviation, and (3) better methods of timely distribution of both pilot reports and ground weather data. The development of the discrete address beacon system data link, Doppler weather radar network, and various information processing techniques are described.
the Weather Surveillance Radar - 1988 Doppler (WSR-88D) . In a sister project to LEAD, the CASA project  is developing small scale regional Doppler radars (i.e. NetRad radars) of a size that can be mounted on cell and frequency than the WSR- 88D Doppler radar. Finally, large-scale computational grids, such as Teragrid [1
Gleason, Byron Edward
different case events. These events were classified into one of three weather system classifications. The classifications were based on two criteria, synoptic conditions and the storms radar signature. Radar data were collected from five levels above...
Nduwayezu, E.; Kanevski, M.; Jaboyedoff, M.
Support to climate change adaptation is a priority in many International Organisations meetings. But is the international approach for adaptation appropriate with field reality in developing countries? In Rwanda, the main problems will be heavy rain and/or long dry season. Four rainfall seasons have been identified, corresponding to the four thermal Earth ones in the south hemisphere: the normal season (summer), the rainy season (autumn), the dry season (winter) and the normo-rainy season (spring). The spatial rainfall decreasing from West to East, especially in October (spring) and February (summer) suggests an «Atlantic monsoon influence» while the homogeneous spatial rainfall distribution suggests an «Inter-tropical front » mechanism. The torrential rainfall that occurs every year in Rwanda disturbs the circulation for many days, damages the houses and, more seriously, causes heavy losses of people. All districts are affected by bad weather (heavy rain) but the costs of such events are the highest in mountains districts. The objective of the current research is to proceed to an evaluation of the potential rainfall risk by applying advanced geospatial modelling tools in Rwanda: geostatistical predictions and simulations, machine learning algorithm (different types of neural networks) and GIS. The research will include rainfalls variability mapping and probabilistic analyses of extreme events.
Morales, C.; Machado, L. A. T.; Angelis, C. F.
Over the past 2 years, two rainfall estimation algorithms (Hydroestimator and USProb) have been operational at the Satellite Division of the Brazilian Space Research Institute (INPE). Hydroestimator is an IR technique that was based on the NESDIS Autoestimator algorithm, while USProb is a continental microwave retrieval that was developed for the Amazon Region. Besides these two schemes, another algorithm that makes use of IR and VIS channels and a cloud tracking technique (Fortracc) have been developed. During the conference, two years of rainfall estimation over Brazil will be used to diagnose the performance of such algorithms. These analysis will be concentrated on instantaneous, hourly, daily and monthly statistics in addition to the diurnal cycle representation. As the ground thruth, quality control rain guages and weather radar rain maps are employed over most part of Brazil. Moreover, regional statistics will be employed due to different precipitating systems acting in Brazil, i.e., the nothern part hold most of tropical convection, while northeast show warm cloud systems and the south, southeast and center Brazil have a combination of tropical convection, cold fronts, mesoscale convective systems and localized convection. Finally at the end of the presention, few annoucements will be made on behalf of GPM-Brazil. In that opportunity it will be shown the 2010 calendar activity for the Brazilian Field Campaigns as part of the Precipitation Measuring Mission (PMM) validation program.
Bunch, Brian (Inventor)
An embodiment of the supplemental weather display system presents supplemental weather information on a display in a craft. An exemplary embodiment receives the supplemental weather information from a remote source, determines a location of the supplemental weather information relative to the craft, receives weather information from an on-board radar system, and integrates the supplemental weather information with the weather information received from the on-board radar system.
Robinson, M.; Kulie, M. S.; Marks, D. A.; Wolff, D. B.; Ferrier, B. S.; Amitai, E.; Silberstein, D. S.; Fisher, B. L.; Wang, J.; Einaudi, Franco (Technical Monitor)
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. Since the successful 1997 launch of the TRMM satellite, GV rainfall estimates have demonstrated systematic improvements directly related to improved radar and rain gauge data, modified science techniques, and software revisions. Improved rainfall estimates have resulted in higher quality GV rainfall products and subsequently, much improved evaluation products for the satellite-based precipitation estimates from TRMM. This presentation will demonstrate how TRMM GV rainfall products created in a semi-automated, operational environment have evolved and improved through successive generations. Monthly rainfall maps and rainfall accumulation statistics for each primary site will be presented for each stage of GV product development. Contributions from individual product modifications involving radar reflectivity (Ze)-rain rate (R) relationship refinements, improvements in rain gauge bulk-adjustment and data quality control processes, and improved radar and gauge data will be discussed. Finally, it will be demonstrated that as GV rainfall products have improved, rainfall estimation comparisons between GV and satellite have converged, lending confidence to the satellite-derived precipitation measurements from TRMM.
Zipser, Edward J.; Mcguirk, James P.
By completing hardware installation, preparing for comparative studies of SSM/I, radar, and lightning data, it is believed that this will be a powerful combination for evaluating the global distribution of tropical rainfall, and the vertical distribution of latent heating, with strong application to algorithms for use on TRMM, EOS-A, and future GOES spacecraft. Potential data bases will be surveyed, about 5 case studies with surface rainfall, radar, lightning, and sounding data will be identified. SSM/I algorithms will be used to identify convective regions of MCSs. A catalog will be developed of the global profile of heavy tropical rainfall, and how these zones are organized within larger tropical weather systems. Beginning with the first few months of SSM/I data distributed over WetNet, SSM/I radiances will be compared with TOVS radiance (moisture and thermal) and OLR observations. The purpose is to improve understanding of how real world water vapor profiles in the tropical atmosphere are perceived by SSM/I precipitable water algorithm and, at the same time, by the TOVS water vapor channel.
The Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) 2A23 algorithm classifies rain echo as stratiform or convective while the 2A25 algorithm corrects vertical profiles of radar reflectivity for attenuation ...
Mote, Thomas L.; Lacke, Matthew C.; Shepherd, J. Marshall
Ground-based weather radar from Peachtree City, GA, is used to examine the distribution of summer precipitation in northern Georgia, including metropolitan Atlanta, during June-August of 2002-2006. The study included 194 ``synoptically benign'' days with a maritime tropical air mass type. Areas in eastern metropolitan Atlanta are shown to have 30% more rainfall during these days than areas west of the city. Both precipitation amount and frequency were enhanced up to 80 km to the east of the urban core of Atlanta. A precipitation maxima northeast of Atlanta occurs near a precipitation anomaly and lightning flash density anomaly identified in previous studies. An hourly analysis of precipitation data demonstrates that the enhanced precipitation on the periphery of the urban core is most evident from 00-05 UTC (19-00 LST). This study is the first to use ground-based radar precipitation estimates in an attempt to quantify the impact of urbanization on precipitation.
Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles
The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.
Antonini, Andrea; Melani, Samantha; Mazza, Alessandro; Ortolani, Alberto; Gozzini, Bernardo; Corongiu, Manuela; Cristofori, Simone
Monitoring weather phenomena from radar has an essential role in nowcasting applications. As one of the most useful sources of quantitative precipitation estimation, rainfall radar analysis can be a very useful research tool in supporting methods for rainfall forecasting. Its short-term prediction is often needed in various meteorological and hydrological applications where accurate prediction of rainfall is essential from national service and civil protection forecasting up to agriculture and urban issues. Very recently, Tuscany region (central Italy) is equipped with two X-band radars with a maximum range of 108 km, a beam width of 3° and a high spatial resolution (i.e., radial resolution up to 90m), located in Livorno and Cima del Monte (Elba island) sites. The first system is property of Livorno's port Authority, the second one of Consorzio LaMMA (Laboratory of Monitoring and Environmental Modelling for the sustainable development) who has installed it in the framework of "RESMAR - Environmental Resources in the MARitime Space" activities, a strategic project, financed in the framework of the European Cross-Border Cooperation Programme Italy-France "Maritime", coordinated by the Liguria Region Administration. Both systems are managed by LaMMA. The cross-border sharing of such relevant meteorological observation instruments and the integration of these data with existing tools and methodologies is intended to improve operational regional weather services in nowcasting activities and their impacts on the territory, as those related to LaMMA daily issues. This sharing is widely promoted within RESMAR project between the different partner regions (ARPA-Sardinia, Meteo-France and Liguria). The integration of these data with other complementary and ancillary measurements is also needed to increase the reliability and accuracy of radar measurements in view of both a better meteorological phenomena understanding and quantitative precipitation estimation. The use of satellite data largely improves the spatial and temporal information on the events, filling up the gaps of uneven data distribution; for this issue LaMMA has multi-year skills in the acquisition and processing of geostationary and polar satellites. The regional raingauge network and meteorological stations will be instead used to obtain useful information both to calibration (as those related to radar reflectivity - rain rate relationships) and validation processes. The radar system and its mosaicking will be presented, as well as some preliminary products.
Scanlon, Charles H.
The primary objective is to develop an advanced pilot weather interface for the flight deck and to measure its utilization and effectiveness in pilot reroute decision processes, weather situation awareness, and weather monitoring. Identical graphical weather displays for the dispatcher, air traffic control (ATC), and pilot crew should also enhance the dialogue capabilities for reroute decisions. By utilizing a broadcast data link for surface observations, forecasts, radar summaries, lightning strikes, and weather alerts, onboard weather computing facilities construct graphical displays, historical weather displays, color textual displays, and other tools to assist the pilot crew. Since the weather data is continually being received and stored by the airborne system, the pilot crew has instantaneous access to the latest information. This information is color coded to distinguish degrees of category for surface observations, ceiling and visibilities, and ground radar summaries. Automatic weather monitoring and pilot crew alerting is accomplished by the airborne computing facilities. When a new weather information is received, the displays are instantaneously changed to reflect the new information. Also, when a new surface or special observation for the intended destination is received, the pilot crew is informed so that information can be studied at the pilot's discretion. The pilot crew is also immediately alerted when a severe weather notice, AIRMET or SIGMET, is received. The cockpit weather display shares a multicolor eight inch cathode ray tube and overlaid touch panel with a pilot crew data link interface. Touch sensitive buttons and areas are used for pilot selection of graphical and data link displays. Time critical ATC messages are presented in a small window that overlays other displays so that immediate pilot alerting and action can be taken. Predeparture and reroute clearances are displayed on the graphical weather system so pilot review of weather along the route can be accomplished prior to pilot acceptance of the clearance. An ongoing multiphase test series is planned for testing and modifying the graphical weather system. Preliminary data shows that the nine test subjects considered the graphical presentation to be much better than their current weather information source for situation awareness, flight safety, and reroute decision making.
Topics related to radar systems are considered, taking into account intrapulse polarization agile radar, search strategies of phased array radars, design and performance considerations in modern phased array radar, a new generation airborne synthetic aperture radar system, results from a new dual band radar for sea surface and aircraft search, modular survivable radar for battlefield surveillance applications, and the Dolphin naval surveillance radar. Other subjects explored are concerned with sequential detection and MTI, adaptive processing techniques, HF/VHF radar, coherent radar processing, multisite radar operation, radar sea clutter, air traffic control, simulation and data processing, aspects of target recognition, low probability of intercept radar and passive operation, signal processing, low sidelobe antennas, and radar returns from weather and land. Attention is also given to beam forming with phased array antennas, optical fiber networks for signal distribution and control in phased array radars, and radar tracking systems. For individual items see A84-10752 to A84-10841
Yi, J.; Choi, C.
Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.
Bhattacharya, Biswa; Tohidul Islam, Md.
This research focuses on the flood risk of the Haor region in the north-eastern part of Bangladesh. The prediction of the hydrological variables at different spatial and temporal scales in the Haor region is dependent on the influence of several upstream rivers in the Meghalaya catchment in India. Limitation in hydro-meteorological data collection and data sharing issues between the two countries dominate the feasibility of hydrological studies, particularly for near-realtime predictions. One of the possible solutions seems to be in making use of the variety of satellite based and meteorological model products for rainfall. The abundance of a variety of rainfall products provides a good basis of hydrological modelling of a part of the Ganges and Brahmaputra basin. In this research the TRMM data and rainfall forecasts from ECMWF have been compared with the scarce rain gauge data from the upstream Meghalaya catchment. Subsequently, the TRMM data and rainfall forecasts from ECMWF have been used as the meteorological input to a rainfall-runoff model of the Meghalaya catchment. The rainfall-runoff model of Meghalaya has been developed using the DEM data from SRTM. The generated runoff at the outlet of Meghalaya has been used as the upstream boundary condition in the existing rainfall-runoff model of the Haor region. The simulation results have been compared with the existing results based on simulations without any information of the rainfall-runoff in the upstream Meghalaya catchment. The comparison showed that the forecasting lead time has been substantially increased. As per the existing results the forecasting lead time at a number of locations in the catchment was about 6 to 8 hours. With the new results the forecasting lead time has gone up, with different levels of accuracy, to about 24 hours. This additional lead time will be highly beneficial in managing flood risk of the Haor region of Bangladesh. The research shows that satellite based rainfall products and rainfall forecasts from meteorological models can be very useful in flood risk management, particularly for data scarce regions and/or transboundary regions with data sharing issues. Keywords: flood risk management, TRMM, ECMWF, flood forecasting, Haor, Bangladesh. Abbreviations: TRMM: Tropical Rainfall Measuring Mission ECMWF: European Centre for Medium-Range Weather Forecasts DEM: Digital Elevation Model SRTM: Shuttle Radar Topography Mission
Severe weather, such as cyclones, heavy rainfall, outburst of cold air, etc., results in great disaster all the world. It is the mission for the scientists to design a warning system, to predict the severe weather systems and to reduce the damage of the society. In Taiwan, National Satellite Project Office (NSPO) initiated ROCSAT-3 program at 1997. She scheduled the Phase I conceptual design to determine the mission for observation weather system. Cooperating with National Center of Atmospheric Research (NCAR), NSPO involved an international cooperation research and operation program to build a 32 GPS satellites system. NCAR will offer 24 GPS satellites. The total expanse will be US 100 millions. NSPO also provide US 80 millions for launching and system engineering operation. And NCAR will be responsible for Payload Control Center and Fiducial Network. The cooperative program contract has been signed by Taiwan National Science Council, Taipei Economic Cultural Office of United States and American Institute in Taiwan. One of the payload is COSMIC, Constellation Observation System for Meteorology, Ionosphere and Climate. It is a GPS meteorology instrument system. The system will observe the weather information, e. g. electron density profiles, horizontal and vertical TEC and CFT scintillation and communication outage maps. The mission is to obtain the weather data such as vertical temperature profiles, water vapor distribution and pressure distribution over the world for global weather forecasting, especially during the severe weather period. The COSMIC Conference held on November, 1998. The export license was also issued by Department of Commerce of Unites States at November, 1998. Recently, NSPO begun to train their scientists to investigate the system. Scientists simulate the observation data to combine the existing routine satellite infrared cloud maps, radar echo and synoptic weather analysis for severe weather forecasting. It is hopeful to provide more accurate weather analysis for forecasting and decreasing the damage of the disasters over the area concerned.
Dorman, C. E.
Communications systems operating at frequencies in excess of 10 GHz are degraded significantly by rainfall. To provide the information needed for design of these millimeter wave systems, rain attentuation models were developed and data bases of propagation related information were accumulated. These data bases were developed based on the signal level measurements of geostationary satellite beacons at selected frequencies. Groundbased radar reflection measurements were able to develop data bases for system design. The rain attenuation models allow accurate correlation between the rain rate and the attenuation.
Chen, Philip C.
Modifications made to the Central Weather Processor (CWP) project are discussed. In 1987, the development plan was revised and the CWP was split into the following parts: a meteorological weather processor and a realtime weather processor (RWP). The JPL is in charge of RWP development. Consideration is given to the major product categories (NEXRAD products, alphanumeric weather products, binary encoded products, graphic products), and the system architecture (the individual radar processor, the radar mosaic processor, and the communication and control processor).
Achleitner, Stefan; Fach, Stefan; Einfalt, Thomas; Rauch, Wolfgang
Nowcasting of rainfall may be used additionally to online rain measurements to optimize the operation of urban drainage systems. Uncertainties quoted for the rain volume are in the range of 5% to 10% mean square error (MSE), where for rain intensities 45% to 75% MSE are noted. For larger forecast periods up to 3 hours, the uncertainties will increase up to some hundred percents. Combined with the growing number of real time control concepts in sewer systems, rainfall forecast is used more and more in urban drainage systems. Therefore it is of interest how the uncertainties influence the final evaluation of a defined objective function. Uncertainty levels associated with the forecast itself are not necessarily transferable to resulting uncertainties in the catchment's flow dynamics. The aim of this paper is to analyse forecasts of rainfall and specific sewer output variables. For this study the combined sewer system of the city of Linz in the northern part of Austria located on the Danube has been selected. The city itself represents a total area of 96 km2 with 39 municipalities connected. It was found that the available weather radar data leads to large deviations in the forecast for precipitation at forecast horizons larger than 90 minutes. The same is true for sewer variables such a CSO overflow for small sub-catchments. Although the results improve for larger spatial scales, acceptable levels at forecast horizons larger than 90 minutes are not reached. PMID:19342810
ten Veldhuis, Marie-claire; van Riemsdijk, Birna
Hydrological analysis of urban catchments requires high resolution rainfall and catchment information because of the small size of these catchments, high spatial variability of the urban fabric, fast runoff processes and related short response times. Rainfall information available from traditional radar and rain gauge networks does no not meet the relevant scales of urban hydrology. A new type of weather radars, based on X-band frequency and equipped with Doppler and dual polarimetry capabilities, promises to provide more accurate rainfall estimates at the spatial and temporal scales that are required for urban hydrological analysis. Recently, the RAINGAIN project was started to analyse the applicability of this new type of radars in the context of urban hydrological modelling. In this project, meteorologists and hydrologists work closely together in several stages of urban hydrological analysis: from the acquisition procedure of novel and high-end radar products to data acquisition and processing, rainfall data retrieval, hydrological event analysis and forecasting. The project comprises of four pilot locations with various characteristics of weather radar equipment, ground stations, urban hydrological systems, modelling approaches and requirements. Access to data processing and modelling software is handled in different ways in the pilots, depending on ownership and user context. Sharing of data and software among pilots and with the outside world is an ongoing topic of discussion. The availability of high resolution weather data augments requirements with respect to the resolution of hydrological models and input data. This has led to the development of fully distributed hydrological models, the implementation of which remains limited by the unavailability of hydrological input data. On the other hand, if models are to be used in flood forecasting, hydrological models need to be computationally efficient to enable fast responses to extreme event conditions. This presentation will highlight ICT-related requirements and limitations in high resolution urban hydrological modelling and analysis. Further ICT challenges arise in provision of high resolution radar data for diverging information needs as well as in combination with other data sources in the urban environment. Different types of information are required for such diverse activities as operational flood protection, traffic management, large event organisation, business planning in shopping districts and restaurants, timing of family activities. These different information needs may require different configurations and data processing for radars and other data sources. An ICT challenge is to develop techniques for deciding how to automatically respond to these diverging information needs (e.g., through (semi-)automated negotiation). Diverse activities also provide a wide variety of information resources that can supplement traditional networks of weather sensors, such as rain sensors on cars and social media. Another ICT challenge is how to combine data from these different sources for answering a particular information need. Examples will be presented of solutions are currently being explored.
Leon, David.; Lasher-Trapp, Sonia; French, Jeffrey; Blyth, Alan; Bennett, Lindsay; Brown, Phil
The COnvective Precipitation E experiment (COPE), which took place over the southwestern peninsula of the UK in Summer 2013, was motivated by a number of convective storms that produced flash flooding, chief among them the Boscastle flood event of 2004. Cloud tops during the Boscastle flood reached temperatures of -15 to -20 °C. Coupled with possible seeding from aloft, it was reasonable to presume that ice processes played an important role in precipitation formation. Some heavy precipitation events were sampled by the suite of ground-based and airborne instruments assembled for COPE, despite the unusually warm and dry weather in the UK at that time. Convective cells during several of these events had tops below the freezing level, or not far above where no ice was observed by the aircraft. Impressively, heavy rainfall was observed at the ground-based X-band radar with reflectivities frequently exceedeeding +60 dBZ. Here we use new in situ observations from the University of Wyoming King Air and the Wyoming Cloud Radar to corroborate reflectivity from the ground-based X-band radar. These observations, along with atmospheric soundings and calculations from a 1D warm rain model, are also utilized to understand the dynamic, thermodynamic and microphysical structure of these heavily precipitating convective cells. These observations lead us to question the prevalent assumption that ice processes are critical to the production of heavy convective precipitation.
Bonelli, P.; Marcacci, P.
Thunderstorms and their ground effects, such as flash floods, hail, lightning, strong winds, and tornadoes, are responsible for most weather damages in northern Italy, especially in the warm season from May to September. A nowcasting and warning system focused on severe thunderstorm events would be useful to reduce risks for people involved in outside activities and for electric, telecommunication, and sensitive industrial business. C-band radar and Lighting Location Systems provide useful, fast and high resolution data for the detection of convective systems and for following their dynamics. The whole of northern Italy is covered by radar with a resolution of 1 km and by a lightning network with a mean accuracy of 0.5 km on the single point of impact. The authors present an algorithm developed for tracking high intensity storm cells by means of radar and lightning data. Application to northern Italy reveals that tracking thunderstorm cells can be used as an alert system that may help prevent damages from extreme weather, as well as allowing for studying the correlation among lightning, rainfall and tornado occurrence. Assessing the algorithm skill is also discussed, and a forecast verification method is described and applied for the duration of a thunderstorm season.
Kelly, Shaun Innes
Synthetic aperture radar is an important tool in a wide range of civilian and military imaging applications. This is primarily due to its ability to image in all weather conditions, during both the day and the night, ...
A new, computerized weather analysis and display system developed by the National Oceanic and Atmospheric Administration (NOAA) is being used to provide air traffic controllers in Colorado with up-to-date information on weather systems that could affect aircraft within their control areas. The system, called PROFS (Prototype Regional Observing and Forecasting Services), was under development for four years at NOAA's Environmental Research Laboratories in Boulder, and is undergoing operational evaluation at the Federal Aviation Administration's (FAA's) Denver Air Route Traffic Control Center in Longmont, Colo. FAA officials see the new system as a first step in upgrading the weather support services for the nation's air traffic control system. Originally created to help National Weather Service personnel with their forecasting duties (Eos, April 13, 1982, p. 233), the PROFS system was specially tailored for aviation use before being installed at the Longmont center. The system uses computers to process weather data from satellites, regional radar, wind profilers, a network of automated weather stations in eastern Colorado, and other sources, some of which are not normally available to forecasters. When this information is collected and formatted, weather personnel at the center can choose from several types of visual display on their terminals, depending on what information they require. The forecasters can then make printed copies of any display and distribute them within moments to controllers who use the information to alert air traffic to storms, wind shifts, and other weather disturbances.
Open problem: Dynamic Relational Models for Improved Hazardous Weather Prediction Amy McGovern1 dis- covery methods for use on mesoscale weather data. Severe weather phenomena such as tornados, thun, current techniques for predicting severe weather are tied to specific characteristics of the radar systems