#Doppler 10 radar software#

Comparison of single- and dual-polarization–based rainfall estimates using NEXRAD data for the NASA Iowa Flood Studies Project. Seo B, Dolan B, Krajewski WF, Rutledge SA, Petersen W. Real-time correction of spatially nonuniform bias in radar rainfall data using rain gauge measurements. RadarZ–RRelationship for summer monsoon storms in Arizona. Morin E, Maddox RA, Goodrich DC, Sorooshian S. A comparison of NEXRAD WSR-88D radar estimates of rain accumulation with gauge measurements for high- and low-reflectivity horizontal gradient precipitation events. Klazura GE, Thomale JM, Kelly DS, Jendrowski P. Comparison of raingage and WSR-88D Stage III precipitation data over the Texas-Gulf basin. Hydrometeorology Group’s Projects and Plans for Improving WSR-88D Rainfall Algorithms and Products, Retrieved from. An exploratory multisensor technique for quantitative estimation of stratiform rainfall. Gourley JJ, Maddox RA, Howard KW, Burgess DW. Rainfall estimation by the WSR-88D for heavy rainfall events. Assessment of uncertainty in Doppler Radar estimated precipitation. Concatenating these two columns results in 8830 ordered pairs. Radar consists of estimated rainfall values in millimeters given by the Doppler radar estimates prior to the precipitation event. Gauge consists of rainfall values in millimeters given by the recording gauge following the precipitation event. The data file (Table 1) comprises two columns of rainfall data Gauge and Radar. Similarly, the rain-gauge data are obtained from the papers’ authors or by digitizing the point data displayed in the respective paper’s diagrams and figures. These standard procedures as detailed by the respective authors relate to the geographical location of radar and gauge. Assume that standard procedures for processing the source data were used for the various papers assembled from the literature. Without the actual source data, the processed data supplied by the respective papers’ authors or digitizing the data directly from the papers used, populated the ordered pairs in the presented data set. Assume that the displayed data points relating to the correlation between Doppler-Radar readings versus measured precipitation, as shown in the various figures of the published papers shown in the references, are adequately processed and suitable for further analysis. The data used in the referenced analysis are from the original, cited manuscripts. There is no need for additional corrections or processing for the published data in the cited references. The gauge data are also the final data as recorded by the gauges at the respective locations. Note that the data used for analysis is not raw data it is the end data obtained by the respective authors after applying standard corrections (if any) to the radar reflectivity and other parameters. Specifically, the plot digitizer ( ), is a Java tool that digitizes data points from scanned plots.

#Doppler 10 radar software#

Pulling from each reference, digitizing software reads graphs and tabulates data for later concatenating.

The data compares Doppler radar derived rainfall estimates with observed local gauge values, spread across storms and geographical domains with the majority categorized via total storm accumulation. Published literature contains data in the form of scatter plots and tables. ĭatasets generated and/or analyzed during the current study are available in the figshare repository. This data is relevant to other researchers involved in investigating the association of Doppler radar data and gauge precipitation estimate relationships. An indication of the estimation error can be determined by comparing the frequency distribution of the source data against the regression equation predictors obtained from the Doppler radar estimates. Researchers may use these rainfall estimates for study purposes by comparing the accuracy of the Doppler radar estimated precipitation with the actual comparative gauge data. Herein we present the ordered data for both Doppler radar precipitation estimates with associated gauge precipitation estimates pulled from ten referenced publications. Processing this signal information yields a rainfall estimate relying on relationships between statistical regression equations and several other parameters.

Prediction of rainfall using Doppler technology relies on synthesizing the signal information that the radars receive back from the atmosphere.