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Robert K. Crane - One of the best experts on this subject based on the ideXlab platform.
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Rain-Rate data base development and Rain-Rate climate analysis
1993Co-Authors: Robert K. CraneAbstract:The single-year Rain-Rate distribution data available within the archives of Consultative Committee for International Radio (CCIR) Study Group 5 were compiled into a data base for use in Rain-Rate climate modeling and for the preparation of predictions of attenuation statistics. The four year set of tip-time sequences provided by J. Goldhirsh for locations near Wallops Island were processed to compile monthly and annual distributions of Rain Rate and of event durations for intervals above and below preset thresholds. A four-year data set of tropical Rain-Rate tip-time sequences were acquired from the NASA TRMM program for 30 gauges near Darwin, Australia. They were also processed for inclusion in the CCIR data base and the expanded data base for monthly observations at the University of Oklahoma. The empirical Rain-Rate distributions (edfs) accepted for inclusion in the CCIR data base were used to estimate parameters for several Rain-Rate distribution models: the lognormal model, the Crane two-component model, and the three parameter model proposed by Moupfuma. The intent of this segment of the study is to obtain a limited set of parameters that can be mapped globally for use in Rain attenuation predictions. If the form of the distribution can be established, then perhaps available climatological data can be used to estimate the parameters rather than requiring years of Rain-Rate observations to set the parameters. The two-component model provided the best fit to the Wallops Island data but the Moupfuma model provided the best fit to the Darwin data.
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space time structure of Rain Rate fields
Journal of Geophysical Research, 1990Co-Authors: Robert K. CraneAbstract:Information on the spatial and temporal statistics of Rain Rate is needed for the design of remote sensing systems for the measurement of areal Rainfall accumulation and for the design of millimeter wave communication systems. In this study, Rain gage and radar data were used to determine empirically the spatial and temporal structure of the Rain process as observed using Rain Rate as a tracer of the atmospheric motions and to test the validity of Taylor's hypothesis for relating their spatial and temporal statistics. Weather radar derived Rain Rate maps were employed to obtain one- and two-dimensional spatial power spectra. Azimuthally averaged two-dimensional spectra displayed the shape predicted for a passive scalar advected by a steady state field of two-dimensional turbulence driven by the input of energy over a narrow band of wave numbers. One-dimensional spatial spectra for a short line of Rain gages had the same spectral shape as the azimuthally averaged spectra obtained from the radar data. Temporal spectra from the gage time series were nearly identical in shape to the one-dimensional spatial spectra if less than a half hour of data were processed to geneRate a spectrum and a constant translation velocity was assumed to relate themore » temporal and spatial scales. For spectra corresponding to longer durations, a match could not be made.« less
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Space‐time structure of Rain Rate fields
Journal of Geophysical Research, 1990Co-Authors: Robert K. CraneAbstract:Information on the spatial and temporal statistics of Rain Rate is needed for the design of remote sensing systems for the measurement of areal Rainfall accumulation and for the design of millimeter wave communication systems. In this study, Rain gage and radar data were used to determine empirically the spatial and temporal structure of the Rain process as observed using Rain Rate as a tracer of the atmospheric motions and to test the validity of Taylor's hypothesis for relating their spatial and temporal statistics. Weather radar derived Rain Rate maps were employed to obtain one- and two-dimensional spatial power spectra. Azimuthally averaged two-dimensional spectra displayed the shape predicted for a passive scalar advected by a steady state field of two-dimensional turbulence driven by the input of energy over a narrow band of wave numbers. One-dimensional spatial spectra for a short line of Rain gages had the same spectral shape as the azimuthally averaged spectra obtained from the radar data. Temporal spectra from the gage time series were nearly identical in shape to the one-dimensional spatial spectra if less than a half hour of data were processed to geneRate a spectrum and a constant translation velocity was assumed to relate themore » temporal and spatial scales. For spectra corresponding to longer durations, a match could not be made.« less
Kevin S Paulson - One of the best experts on this subject based on the ideXlab platform.
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Estimating 1 min Rain Rate distributions from numerical weather prediction
Radio Science, 2017Co-Authors: Kevin S PaulsonAbstract:Internationally recognized prognostic models of Rain fade on terrestrial and Earth-space EHF links rely fundamentally on distributions of 1 min Rain Rates. Currently, in Rec. ITU-R P.837-6, these distributions are geneRated using the Salonen-Poiares Baptista method where 1 min Rain Rate distributions are estimated from long-term average annual accumulations provided by numerical weather prediction (NWP). This paper investigates an alternative to this method based on the distribution of 6 h accumulations available from the same NWPs. Rain Rate fields covering the UK, produced by the Nimrod network of radars, are integRated to estimate the accumulations provided by NWP, and these are linked to distributions of fine-scale Rain Rates. The proposed method makes better use of the available data. It is verified on 15 NWP regions spanning the UK, and the extension to other regions is discussed.
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fractal interpolation of Rain Rate time series
Journal of Geophysical Research, 2004Co-Authors: Kevin S PaulsonAbstract:[1] Meteorological radar databases exist providing Rain Rate maps over areas with a sampling period of 2–15 min. Such two-dimensional, Rain Rate map time series would have wide application in the simulation of Rain scatter and attenuation of millimeter-wave radio networks, if the sampling period were considerably shorter, i.e., of the order of 10 s or less. However, scanning a large radar at this Rate is physically infeasible. This paper investigates a stochastic numerical method to interpolate point Rain Rate time series to shorter sampling periods while conserving the expected first- and second-order statistics. The proposed method should generally be applicable to the temporal interpolation of radar-derived Rain Rate maps. The method is based on the experimentally measured simple-scaling properties of log Rain Rate time series. It is tested against 9 gauge years of rapid response drop-counting Rain gauge data, with a 10 s integration time, collected in the southern UK. The data are subsampled to yield time series with a 10 s Rain Rate measurement every 320, 640, and 1280 s. The subsampled time series are then interpolated back to a 10 s sample interval, and the first- and second-order statistics are compared with the original time series.
Ali Kadhim Lwas - One of the best experts on this subject based on the ideXlab platform.
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Investigation of Time Diversity Gain for Earth to Satellite Link Using Rain Rate Gain
Bulletin of Electrical Engineering and Informatics, 2019Co-Authors: Moktarul Alam, Islam Md. Rafiqul, Khairayu Badron, A R Farah Dyana, M. Rofiqul Hassan, Ali Kadhim LwasAbstract:The utilization of satellites for communication systems has expanded considerably in recent years. C and Ku-bands of frequencies are already congested because of high demand. Future directions of satellite communications are moving towards Ka and V-bands. Earth to satellite communications are moving towards higher frequency bands in future which are more sensitive to environment. Rain causes severe degradation in performances at higher frequency bands specially in tropical regions. Several mitigation techniques are proposed to design reliable system. Time diversity is one of the potential candidate for it. However, time diversity analysis requires measured Rain attenuation data. For future high frequency link design those data are not available at most of the places. This thesis proposes a method to utilize 1-minute Rain Rate to analyze time diversity technique at any desired frequency. This paper proposes a method to utilize 1-minute Rain Rate to analyse time diversity Rain Rate gain. In proposed method, it is assumed that Rain Rate gain with delay can represent Rain attenuation gain with delay for same period of time at same location. The characteristics of Rain Rate and Rain attenuation almost same because the attenuation causes due to Rain. One year measured Rain Rate in Malaysia is used to predict Rain Rate gain. The measured gain at 12.225 GHz signal is compared with that predicted by ITU-R based on Rain Rate measurement and is found good agreement. Hence it is recommended that the time diversity gain can be predicted using measured Rain Rate for any desired frequencies.
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Time Diversity Gain Analysis for Earth to Satellite Link Based on Measured Rain Rate
2018 7th International Conference on Computer and Communication Engineering (ICCCE), 2018Co-Authors: Md Moktarul Alam, Islam Md. Rafiqul, Khairayu Badron, Dyana A.r. Farah, Ali Kadhim LwasAbstract:Earth-to-satellite links are highly affected by propagation impairments especially by Rain that opeRate at frequencies higher than 10 GHz. Therefore, the satellite communication system performance suffers from severe degradation at high frequencies in tropical and equatorial climate. Time diversity is one of the workable technique with suitable time delay between successive transmissions which is proposed by many researchers to mitigate Rain fade. However, time diversity analysis requires measured Rain attenuation data. For future high frequency link design those data are not available at most of the places. This paper proposes a method to utilize 1-minute Rain Rate to analyse time diversity gain at any desirable frequency. In proposed method, it is assumed that Rain Rate with delay can represent Rain attenuation with delay for same period of time at same location. This assumption is valid as long as the attenuation causes due to Rain. One year measured Rain Rate in Malaysia is used to predict Rain attenuation gain. The measured gain at 12.225 GHz signal is compared with that predicted by ITU-R based on Rain Rate measurement and is found good agreement. Hence it is recommended that the time diversity gain can be predicted using measured Rain Rate for any desired frequencies.
R.k. Crane - One of the best experts on this subject based on the ideXlab platform.
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A local model for the prediction of Rain-Rate statistics for Rain-attenuation models
IEEE Transactions on Antennas and Propagation, 2003Co-Authors: R.k. CraneAbstract:A new local model for the prediction of Rain-Rate statistics is presented. Rain-Rate statistics are needed for Rain-attenuation and Rain-interference prediction models. The new model uses 30-year or longer climate data sets to provide parameters for a closed-form Rain-Rate probability distribution model. The required climate data are available for the USA and its territories. The model provides for the prediction of annual and monthly distributions and for the expected year-to-year variations in these distributions. The model was tested against empirical Rain-Rate distributions obtained from long term (five or more year) observation programs in the USA and Canada. It provides the only model available for predicting monthly or seasonal probability distributions. It provides a solution to the worst month distribution estimation problem because distributions may be predicted for each of the months in a year and the worst one is then readily apparent. The model provides monthly and annual distribution predictions that match the observed distributions within the expected uncertainty produced by the intrinsic interannual variations in Rain occurrence.
Jungsoo Yoon - One of the best experts on this subject based on the ideXlab platform.
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On the Use of Threshold for the Ground Validation of Satellite Rain Rate
Advances in Meteorology, 2015Co-Authors: Jungsoo Yoon, Eunho HaAbstract:Ground-truthing is a major problem in the satellite estimation of Rain Rate. This problem is that the measurement taken by the satellite sensor is fundamentally different from the one it is compared with on the ground. Additionally, since the satellite has the limited capability to measure the light Rain Rate exactly, the comparison should also consider the threshold value of satellite Rain Rate. This paper proposes a ground-truth design with threshold for the satellite Rain Rate. This ground-truth design is the generalization of the conventional ground-truth design which considered the only (zero, nonzero) and (nonzero, nonzero) measurement pairs. The mean-square error is used as an index of accuracy in estimating the ground measurement by satellite measurement. An application to the artificial random field shows that the proposed ground-truth design with threshold is valid as the design bias is zero. The same result is also derived in the application to the COMS (Communication, Ocean, and Meteorological Satellite) Rain Rate data in Korea.
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The runoff uncertainty caused by the mismatch between the radar Rain Rate and the topographical information data
Ksce Journal of Civil Engineering, 2015Co-Authors: Jungsoo Yoon, Jeongho ChoiAbstract:Matching the location of the input data, such as the radar Rain Rate and the topographical information data, is very important in the Rainfall-runoff process. If the radar Rain Rate and the topographical information data have different coordinate systems, the locations of the two types of data will not match. Moreover, the wind effect hinders the matching of the locations of the radar Rain Rate and the topographical information data. In this study, the runoff uncertainty caused by the mismatch between the radar Rain Rate and the topographical information data with respect to the horizontal drift distance was quantified. As a result, when the horizontal drift distance of the water drop observed at altitude of 1.5 km was 1 km, the location mismatch between the radar Rain Rate and the topographical information data produced a total volume error of 3.88±6.13% in the 95% confidence interval, a peak flow error of 3.14±6.33%, and a peak time error of 0.34±1.22%. When the horizontal drift distance increased to 4 km, the error of total volume, peak flow, and peak time increased to 7.52±10.27%, 5.96±10.90%, 3.27±23.48%, respectively.
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Effect of threshold on the comparison of radar and Rain gauge Rain Rate
Ksce Journal of Civil Engineering, 2015Co-Authors: Eunho Ha, Jungsoo YoonAbstract:In this study, the effect of threshold applied to the radar Rain Rate on the comparison of the radar and Rain gauge Rain Rate was theoretically examined. The result derived was also evaluated theoretically, using the Bernoulli random field, and empirically, using Gwanaksan Radar data. The results are summarized as follows. (1) In the application to the Bernoulli random field, it was found that the comparison of the radar and Rain gauge Rain Rate with threshold does not introduce any systematic bias. (2) The same results could also be derived in the application to Gwanaksan Radar data. In all cases with several radar bin sizes and thresholds considered, the bias was estimated to be far less than 10% of the mean of the Rain gauge Rain Rate. (3) However, in the comparison with threshold applied to both the radar and Rain gauge Rain Rate, the bias was estimated to be higher than 20%. That is, the systematic bias was introduced. This result indicates that the comparison with threshold applied to both the radar and Rain gauge Rain Rate should not be used.
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interpretation of mean field bias correction of radar Rain Rate using the concept of linear regression
Hydrological Processes, 2014Co-Authors: Cheolsoon Park, Jungsoo YoonAbstract:In this study, the correction problem of mean-field bias of radar Rain Rate was investigated using the concept of linear regression. Three different relationships were reviewed for their slopes to be used as the bias correction factor: Relationship 1 (R1) is based on the conventional linear regression, relationship 2 (R2) is forced to pass the origin and relationship 3 (R3) is the line whose slope is the G/R ratio. In other words, R1 is the regression line connecting the intercept and the mass centre of measurement pairs, R2 is the regression line forced to pass the origin, and R3 is the line connecting the origin and the mass centre. The slopes of all three relationships were reviewed analytically to compare them, and thereby, the effect of zero measurements could be evaluated. Additionally, the effect of using switched independent and dependent variables on the derived slopes was also evaluated. The theoretically derived results were then verified by analysing the Rainfall event on 10–11 August 2010 in Korea. Finally, the difference between the bias-corrected radar Rain Rate and the Rain gauge Rain Rate was quantified by root mean square error and mean error so that it could be used as a measure for the evaluation of bias correction factors. In conclusion, the slope of R2 was found to be the best for the bias correction factor. However, when deciding the slope of this R2, the radar Rain Rate should be used as the independent variable in the low Rain Rate region, and the Rain gauge Rain Rate in the high Rain Rate region above a certain threshold. Copyright © 2013 John Wiley & Sons, Ltd.
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A quality evaluation criterion for radar Rain-Rate data
IAHS-AISH publication, 2012Co-Authors: Jungsoo Yoon, Cheolsoon ParkAbstract:This study proposed a radar Rain-Rate quality criterion (RRQC), a measure of goodness for the radar Rain-Rate. The RRQC proposed is based on the similar concept of total variance in the statistical analysis of variance, which considers both the bias and variability of radar Rain-Rate with respect to the Raingauge Rain-Rate. The RRQC was estimated for three storm events with the raw radar data, along with improved versions based on G/R correction and merging by co-Kriging. Additionally, these radar data were applied to the runoff analysis of the Choongju Dam Basin, Korea. By investigating the relation between the RRQC in the Rain-Rate input and the errors in the runoff output, a minimum quality of radar Rain-Rate applicable to the Rainfall―runoff analysis was explored.
