Subsurface sounders

Airborne or spaceborne electromagnetic systems used to detect subsurface features are discussed. Data are given as a function of resistivity of ground material, magnetic permeability of free space, and angular frequency. It was noted that resistivities vary with the water content and temperature

A satellite-based radar wind sensor

The objective is to investigate the application of Doppler radar systems for global wind measurement. A model of the satellite-based radar wind sounder (RAWS) is discussed, and many critical problems in the designing process, such as the antenna scan pattern, tracking the Doppler shift caused by satellite motion, and backscattering of radar signals from different types of clouds, are discussed along with their computer simulations. In addition, algorithms for measuring mean frequency of radar echoes, such as the Fast Fourier Transform (FFT) estimator, the covariance estimator, and the estimators based on autoregressive models, are discussed. Monte Carlo computer simulations were used to compare the performance of these algorithms. Anti-alias methods are discussed for the FFT and the autoregressive methods. Several algorithms for reducing radar ambiguity were studied, such as random phase coding methods and staggered pulse repitition frequncy (PRF) methods. Computer simulations showed that these methods are not applicable to the RAWS because of the broad spectral widths of the radar echoes from clouds. A waveform modulation method using the concept of spread spectrum and correlation detection was developed to solve the radar ambiguity. Radar ambiguity functions were used to analyze the effective signal-to-noise ratios for the waveform modulation method. The results showed that, with suitable bandwidth product and modulation of the waveform, this method can achieve the desired maximum range and maximum frequency of the radar system

General aviation weather avoidance sensor study

General aviation weather avoidance sensor stud

Ultra low range sidelobe level pulse compression waveform design for spaceborne meteorological radars.

Meteorological measurements from spaceborne radars present several advantages over current passive techniques, due to the radar capability to discriminate backscattered energy in range. However, the system configuration imposes stringent design requirements in order to guarantee cloud and rain detectability, in particular on the radar waveform. Since power is severely restricted on board a satellite, it is necessary to achieve an efficient range resolution with low transmitted power requirements. Pulse compression theory solves the previous conflicting demand, but the transmitted signal needs to be carefully designed in order to allow the significantly large dynamic range (between 60 and 80 dB depending on the type of meteorological target) needed to carry out the measurements. Several pulse compression range sidelobe reduction techniques of differing natures have been investigated and reported in the literature during the past 50 years. A detailed survey of the most relevant range sidelobe supression procedures has been carried out in order to identify the most suitable frequency modulation candidates which are potentially capable of meeting the stringent specifications of spaceborne radar meteorology. Novel pulse compression waveform design techniques have also been developed, employing linear FM predistortion functions and asymmetric frequency modulation laws, which provide excellent performance in terms of range sidelobe level (below -60 dB) and Doppler tolerance. Different options for the provision of a rain mode for the RA-2 Radar Altimeter (due to fly on European Space Agency ENVISAT satellite) are described, based on altimetry linear FM full-deramp technique concepts. Finally, amplitude modulated pulse compression waveform design alternatives are analysed for the MACSIM radar (Millimetre wave Active Cloud Structure Imaging Mission, European Space Agency Pre Phase A Study), which allow to measure different type of clouds within the Mission required radiometric resolution accuracy

POLAR DATA HEADER FORMAT

This document refers to the file format for polar reflectivity, velocity moments and dual polarisation parameters collected by the processing systems at radar sites around the UK, and the single parameters data files created by the central processing system at the UK Met Office headquarters

Meteorological radar facility. Part 1: System design

A compilation of information regarding systems design of space shuttles used in meteorological radar probes is presented. Necessary radar equipment is delineated, while space system elements, calibration techniques, antenna systems and other subsystems are reviewed

Applied Radar Meteorology

This is a textbook focused on operational and other aspects of applied radar meteorology. Its primary purpose is to serve as a text for upper-level undergraduates and graduate students studying meteorology, who wish to work as professional operational meteorologists in the U.S. National Weather Service or the Air Force Weather Agency. In addition to a detailed description of operational weather radar systems operating in the United States, this text also provides a brief historical overview of the subject as well as a basic review of the physics of electromagnetic radiation and other theoretical aspects of weather radar. The last two chapters discuss a sample of other radar systems (such as the Doppler on Wheels and the Canadian and European operational networks), and future directions of weather radar, including its use as an input for high-resolution, rapid refresh computer models

Radar and satellite observations of precipitation: space time variability, cross-validation, and fusion

2017 Fall.Includes bibliographical references.Rainfall estimation based on satellite measurements has proven to be very useful for various applications. A number of precipitation products at multiple time and space scales have been developed based on satellite observations. For example, the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center has developed a morphing technique (i.e., CMORPH) to produce global precipitation products by combining existing space-based observations and retrievals. The CMORPH products are derived using infrared (IR) brightness temperature information observed by geostationary satellites and passive microwave-(PMW) based precipitation retrievals from low earth orbit satellites. Although space-based precipitation products provide an excellent tool for regional, local, and global hydrologic and climate studies as well as improved situational awareness for operational forecasts, their accuracy is limited due to restrictions of spatial and temporal sampling and the applied parametric retrieval algorithms, particularly for light precipitation or extreme events such as heavy rain. In contrast, ground-based radar is an excellent tool for quantitative precipitation estimation (QPE) at finer space-time scales compared to satellites. This is especially true after the implementation of dual-polarization upgrades and further enhancement by urban scale X-band radar networks. As a result, ground radars are often critical for local scale rainfall estimation and for enabling forecasters to issue severe weather watches and warnings. Ground-based radars are also used for validation of various space measurements and products. In this study, a new S-band dual-polarization radar rainfall algorithm (DROPS2.0) is developed that can be applied to the National Weather Service (NWS) operational Weather Surveillance Radar-1988 Doppler (WSR-88DP) network. In addition, a real-time high-resolution QPE system is developed for the Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) Dallas-Fort Worth (DFW) dense radar network, which is deployed for urban hydrometeorological applications via high-resolution observations of the lower atmosphere. The CASA/DFW QPE system is based on the combination of a standard WSR-88DP (i.e., KFWS radar) and a high-resolution dual-polarization X-band radar network. The specific radar rainfall methodologies at Sand X-band frequencies, as well as the fusion methodology merging radar observations at different temporal resolutions are investigated. Comparisons between rainfall products from the DFW radar network and rainfall measurements from rain gauges are conducted for a large number of precipitation events over several years of operation, demonstrating the excellent performance of this urban QPE system. The real-time DFW QPE products are extensively used for flood warning operations and hydrological modelling. The high-resolution DFW QPE products also serve as a reliable dataset for validation of Global Precipitation Measurement (GPM) satellite precipitation products. This study also introduces a machine learning-based data fusion system termed deep multi-layer perceptron (DMLP) to improve satellite-based precipitation estimation through incorporating ground radar-derived rainfall products. In particular, the CMORPH technique is applied first to derive combined PMW-based rainfall retrievals and IR data from multiple satellites. The combined PMW and IR data then serve as input to the proposed DMLP model. The high-quality rainfall products from ground radars are used as targets to train the DMLP model. In this dissertation, the prototype architecture of the DMLP model is detailed. The urban scale application over the DFW metroplex is presented. The DMLP-based rainfall products are evaluated using currently operational CMORPH products and surface rainfall measurements from gauge networks