Summary of the High Ice Water Content (HIWC) RADAR Flight Campaigns

NASA and the FAA conducted two flight campaigns to quantify onboard weather radar measurements with in-situ measurements of high concentrations of ice crystals found in deep convective storms. The ultimate goal of this research was to improve the understanding and develop onboard weather radar processing to detect regions of high ice water content ahead of an aircraft and enable tactical avoidance of the potentially hazardous conditions. Both High Ice Water Content (HIWC) RADAR campaigns utilized the NASA DC-8 Airborne Science Laboratory which was equipped with a Honeywell RDR-4000 weather radar and icing instruments to characterize the ice crystal clouds. The purpose of this paper is to summarize how these campaigns were conducted and highlight key results

Doppler Spectrum Estimation by Ramanujan Fourier Transforms

The Doppler spectrum estimation of a weather radar signal in a classic way can be made by two methods, temporal one based in the autocorrelation of the successful signals, whereas the other one uses the estimation of the power spectral density PSD by using Fourier transforms. We introduces a new tool of signal processing based on Ramanujan sums cq(n), adapted to the analysis of arithmetical sequences with several resonances p/q. These sums are almost periodic according to time n of resonances and aperiodic according to the order q of resonances. New results will be supplied by the use of Ramanujan Fourier Transform (RFT) for the estimation of the Doppler spectrum for the weather radar signal

The Federal Aviation Administration/Massachusetts Institute of Technology (FAA/MIT) Lincoln Laboratory Doppler weather radar program

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

Research relative to weather radar measurement techniques

Research relative to weather radar measurement techniques, which involves some investigations related to measurement techniques applicable to meteorological radar systems in Thailand, is reported. A major part of the activity was devoted to instruction and discussion with Thai radar engineers, technicians, and meteorologists concerning the basic principles of radar meteorology and applications to specific problems, including measurement of rainfall and detection of wind shear/microburst hazards. Weather radar calibration techniques were also considered during this project. Most of the activity took place during two visits to Thailand, in December 1990 and February 1992

Pengaruh Penerapan Quality Control Data Radar Terhadap Akurasi Estimasi Curah Hujan Di Wilayah Pontianak Dan Sekitarnya

Weather radar operational have a limitation that leads to a quality reduction of radar rainfall estimation, such as interference at Pontianak’s weather radar. The application of 3D Clutter Map and Data Processing (3DCDP),  Brightband Echo Correction (BBC), and Z–Based Attenuation Correction (ZATC) which include in post–processing QC is the common procedure of radar limitation mitigation. This procedure applied to data of Pontianak weather radar over 1 January 2019 – 31 December 2019. The QC implemetation effect observed qualitatively and quantitatively by compare radar’s product before and after QC implementation. Data of radar rainfall estimation compared with rainfall observation data from AWS/ARG, and validated with RMSE and ME values. The comparison of the weather radar image shows that the interference and clutter around the weather radar is reduced. According to 19 validation value on the 10 cases of chosen rain, 18 value shows QC’s increased the accuracy of radar rainfall estimation, though insignificant and still underestimate

Bayesian statistical analysis of ground-clutter for the relative calibration of dual polarization weather radars

A new data processing methodology, based on the statistical analysis of ground-clutter echoes and aimed at investigating the stability of the weather radar relative calibration, is presented. A Bayesian classification scheme has been used to identify meteorological and/or ground-clutter echoes. The outcome is evaluated on a training dataset using statistical score indexes through the comparison with a deterministic clutter map. After discriminating the ground clutter areas, we have focused on the spatial analysis of robust and stable returns by using an automated region-merging algorithm. The temporal series of the ground-clutter statistical parameters, extracted from the spatial analysis and expressed in terms of percentile and mean values, have been used to estimate the relative clutter calibration and its uncertainty for both co-polar and differential reflectivity. The proposed methodology has been applied to a dataset collected by a C-band weather radar in southern Italy

The application of cellular automata to weather radar

A possible cellular automaton approach to weather (and in particular rainfall) modelling is considered. After posing a paradigm problem in a manner reminiscent of a numerical PDE solver and showing that the general approach appears to be valid, we consider some more detailed modelling and comment on how this could be used to construct a genuine finite-state cellular automaton