We present the first-light airborne measurements of a new W-band atmospheric radar, part of the CloudCube instrument. CloudCube is a multifrequency, ultra-compact, low-cost, modular radar system for vertical profiling of clouds, convection, and precipitation structures and dynamics from space. The instrument employs a novel radar architecture that directly upconverts the baseband signal to the RF band, eliminating the need for intermediate frequencies or further multiplication schemes. This architecture, combined with pulse compression techniques, offers a straightforward and effective solution while achieving the necessary performance and robustness for airborne or spaceborne radar instruments. The W-band channel was installed and operated aboard NASA’s DC-8 Airborne Laboratory, completing two test flights over the coast of California and operated as a technology demonstration during science flights as part of the CPEX field deployment. A detailed pulse compression validation and comparison of reflectivity profiles across multiple frequency bands demonstrate the instrument’s performance for atmospheric profiling.

The development of radar systems operating at G-band (110 - 300 GHz) with small size, weight, and power requirements can offer new possibilities for probing clouds and precipitation from space and lead to novel mission concepts. To advance the technology needed to achieve such objective, a ground-based G-band Doppler radar prototype for atmospheric profiling has been developed and demonstrated with different targets. This article describes the radar architecture and discusses the instrument calibration and reflectivity and Doppler velocity measurements of clouds and precipitation.

This article presents a novel method to retrieve spectral widths from measurements of spaceborne Doppler profiling radars (SDPRs) operating in low-Earth orbit. The proposedExplicit Sy-Tanelli (ExpliSyT)approach is based on a formulation of the Doppler broadening in terms of the distributions of reflectivity and velocity in the footprint. This formulation makes it possible to estimate the broadening and remove it from the spectral-width measurement. Two implementations of the ExpliSyT correction are described: 1) a numerical implementation that uses Wiener’s deconvolution and 2) an analytical implementation based on Taylor expansions of the radar observations. The ExpliSyT corrections enable retrievals of higher-order Doppler information, such as posterior power spectra. Results are shown for simulations of the radar of the Earth Cloud Aerosol Radiation Explorer (EarthCARE developed by the European and Japanese space agencies) and a Displaced Phase Center Antenna (DPCA) configuration, for which the ExpliSyT corrections perform significantly better. A novelcanonical Doppler resampling diagramis introduced to explain the correlation between nonuniform beamfilling (NUBF) and spectral broadening. This tool shows that: 1) the NUBF of reflectivity modulates the spacecraft-induced spectral broadening and 2) the NUBF of velocity can either broaden orshrinkthe Doppler spectrum. This spectral shrinkage, although important, is not typically thought of when dealing with spaceborne Doppler radars. The ability to estimate spectral widths accurately from space paves the way for future microphysical and dynamical characterizations of hydrometeors in shear or turbulence.

We introduce a novel RF-photonics receiver concept for high performance ultra-compact 94 GHz radars optimized for cloud and precipitation profiling, planetary boundary layer observations, altimetry and surface scattering measurements. The new receiver architecture offers compelling advantages over traditional electronic implementations, including reduced size, weight and power (SWaP), lower system noise leading to improved sensitivity and a W-band LO with ultra-low phase noise to enable long pulse lengths needed for most compact spaceborne radar systems.

This article presents a new method to retrieve dynamic information from spaceborne Doppler radar observations. The method is based on a Complex Convolution Doppler Resampling (CConDoR) formulation, which links the spaceborne pulse-pair correlation measurements to high-resolution pulse-pair products that are not affected by the spacecraft motion. The CConDoR formalism allows to easily simulate Doppler products (forward simulations) via convolution products. The CConDoR representation enables also retrievals by complex deconvolution. This approach is illustrated using a Wiener deconvolution algorithm. Results are shown for simulations of EarthCARE’s (Earth Cloud Aerosol Radiation Explorer developed by the European and Japanese space agencies) radar. The proposed corrections improve the accuracy of the measured mean velocities (by correcting for non-uniform beam-filling biases) and spectral widths (by correcting for the spectral broadening, which to the best of the Authors’ knowledge is novel).

RainCube (Radar In a CubeSat), developed by the Jet Propulsion Laboratory (JPL) and launched in 2018, was a technology demonstration supported by NASA. RainCube’s radar is the first spaceborne profiling radar fitting on a platform as small as a 6U ($10\times 20\times 30\,\,\mathrm {cm^{3}}$) CubeSat. This article shows how, despite its smaller size compared to traditional spaceborne radars, RainCube was able to measure clouds and precipitation in the mid-latitude and intertropical regions. Moreover, since RainCube’s measurements are oversampled in the along-track (AT) direction, the horizontal resolution can be enhanced by a robust Wiener deconvolution algorithm. After more than two and a half years of operation, the RainCube mission came to an end on 24 December 2020. The collected record of Ka-band radar profiles compares favorably to collocated measurements from other ground-based and spaceborne radars both radiometrically and geophysically. The examples of multiradar collocations also provide some insights into the potential of constellations of spaceborne radars to study clouds and storms.

This paper presents some of the first nearly simultaneous observations between TEMPEST-D and RainCube, two CubeSat missions supported by NASA for on-orbit validation of technology for studying the Earth's atmosphere. This paper presents simultaneous observations by a Ka-band radar and multi-frequency millimeter-wave radiometers over precipitation systems, in three widely dispersed locations over the globe. The first storm was near Mexico's Pacific coast, whereas the second storm was over the South Pacific Ocean near the Solomon Islands, and the third storm was near Houston, Texas, USA. The comparisons showed good physical consistency between the TEMPEST-D and RainCube observations.

Pulse compression has enabled a new generation of low-cost and compact spaceborne weather radar systems. To successfully utilize pulse compression techniques for cloud and precipitation applications, the effects of Doppler-range migration must be considered during the design and operation of the radar. Pulse compression for spaceborne weather applications introduces additional interdependence between the radar system and the operations when compared with traditional pulsed radar systems, primarily as a result of the large platform velocities. Pulse compression signals for weather radar can be simulated with high fidelity to predict and optimize the radar's performance. In this article, we evaluate the pulse compression performance of RainCube, a Ka-band precipitation radar in a CubeSat, through analysis and comparison of observations and radar simulations. Through these comparisons, design and operational considerations for pulse compression weather radar are discussed. This work shows that the optimal pointing angle for RainCube to achieve the finest vertical resolution is not at nadir, but when pointing forward approximately 2.25°, in the direction of the spacecraft's orbit.

Previous work has shown that the relatively large resolution volume of spaceborne precipitation radars can affect precipitation measurements in several ways. During the Olympic Mountains Experiment (OLYMPEX), Ku- and Ka-band airborne radar measurements of precipitation were obtained during two Global Precipitation Measurement (GPM) overpasses, one case over land and one case over ocean. The authors compare the GPM-measured radar quantities with the same quantities inferred from the higher spatial resolution airborne radar data. Differences include smaller maximum reflectivity and path attenuation and more significant surface clutter in mountainous areas for GPM.

The recent successful space-borne demonstration of a miniaturized CubeSat precipitation radar is highlighted. The low cost of such a radar, together with the availability of small satellite, platforms to carry it, now make it feasible to consider employing a more distributed approach to observe important atmospheric processes that relate to precipitation. An approach to quantify the transport of water and air by deep convection is described based on a clustering of small radar satellites providing measurements seconds apart. This strategy now adds time as a new dimension for observing such processes. A mission concept, referred to as D-train, comprised of a train of three satellites 30, 90, and 120 s apart is described, and the expected performance of it for providing measures of convective transport is examined based on a large ensemble of simulations of convection with an advanced cloud-resolving model.

RainCube (Radar in a CubeSat) is a technology demonstration mission to enable Ka-band precipitation radar technologies on a low-cost, quick-turnaround platform. The 6U CubeSat currently in orbit features a radar payload built by the Jet Propulsion Laboratory (JPL) and a spacecraft bus and operations provided by Tyvak Nano-Satellite Systems. Following the deployment of the half-meter parabolic antenna, the radar first observed rainfall over Mexico. The mission continues to operate and has met all requirements through repeated observations of precipitation in the atmosphere. RainCube is funded through the Science Mission Directorate's (SMD) Research Opportunities in Space and Earth Science (ROSES) 2015 In-Space Validation of Earth Science Technologies (InVEST) solicitation with the goal of raising the instrument TRL to 7.

By comparing the observations of heavy storms performed by the Dual-frequency Precipitation Radar (DPR) and the corresponding hydrometeor classification based on ground-based polarimetric measurements of the Next Generation Weather Radar (NEXRAD) we showed that the DPR measurements are heavily affected by non-uniform beam filling (NUBF). The presence of heavily rimed particles within the instrument field of view generates significant signal enhancements at the Ka band caused by multiple scattering (MS). MS and NUBF introduce large ambiguities in the estimate of effective reflectivity below the freezing level (FL), especially at Ka band, which strongly reduces DPR capabilities for detecting hail at the ground.

RainCube (Radar in a CubeSat) is a technology demonstration mission to enable Ka-band precipitation radar technologies on a low-cost, quick-turnaround platform. The mission is manifested for an ISS deployment with the ELaNa-23 launch, currently scheduled in May, 2018. Radar instruments have often been regarded as unsuitable for small satellite platforms due to their traditionally large size, weight, and power. The Jet Propulsion Laboratory (JPL) has developed a novel architecture compatible with the 6U class. The RainCube mission will validate two key technologies in the space environment - a miniaturized Ka-band precipitation profiling radar that occupies ~ 2.5U and a 0.5m Ka-band deployable parabolic antenna stowed within 1.5U. The spacecraft bus is developed by Tyvak Nanosatellite Systems, who will be responsible for integration of the flight system and mission operations. RainCube is funded through the Science Mission Directorate's (SMD) Research Opportunities in Space and Earth Science (ROSES) 2015 In-Space Validation of Earth Science Technologies (InVEST) solicitation with the goal of raising the instrument TRL to 7.

A tunable G-band frequency-modulated continuous-wave radar system has been developed and used to perform differential absorption atmospheric humidity measurements for the first time. The radar's transmitter uses high- power-handling GaAs Schottky diodes to generate between 15-23 dBm over a 10-GHz bandwidth near 183 GHz. By virtue of a high-isolation circular polarization duplexer, the monostatic radar's receiver maintains a noise figure of about 7 dB even while the transmitter is on. With an antenna gain of 40 dB, high-SNR detection of light rain is achieved out to several hundred meters distance. Owing to the strong spectral dependence of the atmospheric absorption over the upper flank of the 183-GHz water absorption line, range-resolved measurements of absolute humidity can be obtained by ratioing the rain echoes over both range and frequency. Absorption measurements obtained are consistent with models of atmospheric millimeter-wave attenuation, and they demonstrate a new method for improving the accuracy of humidity measurements inside of clouds.

In[1, Fig. 5], the assumed atmospheric conditions were incorrectly stated for the curve showing the millimeter-wave propagation model of excess attenuation at frequencies with respect to 193 GHz. Rather than being for 91% relative humidity (RH) and 289 K, as was stated in[1], the model curve in[1, Fig. 5]was for 50% RH and 289 K. (The experimental measurements are unaffected.) The figure is reproduced here asFig. 1(a), now with correct labeling.

Space-based radar observations have transformed our understanding of Earth over the last several decades. Driven by increasingly complex science questions, space radar missions have grown ever more sophisticated with costs rising often to hundreds of millions of dollars. At the other end of the cost and complexity spectrum, CubeSats have emerged in recent years as a disruptive innovation in the satellite sector and are now considered a means to address targeted science questions in a rapid and affordable manner. CubeSats enable new kinds of constellation-based Earth science observations not previously affordable with traditional spacecraft. Constellations of low-cost sensors provide both global spatial and high temporal coverage. As such, CubeSats are not only viable platforms to address current Earth science goals, but they also open a new realm of possibilities for science advancement and unique applications. Radar instruments have often been regarded as unsuitable for small satellite platforms due to their traditionally large size, weight, and power (SWaP). Burgeoning missions such as Radar in a CubeSat (RainCube) and CubeSat Imaging Radar for Earth Science (CIRES), being developed by Jet Propulsion Laboratory and SRI International, respectively, and funded by NASA’s Earth Science Technology Office (ESTO), are slated to dispel this notion. The key to the simplification and miniaturization of the radar subsystems in a manner that still offers compelling science and applications is 1) component technological advancement; and 2) an integrated instrument architecture and mission design that exploits the capabilities offered by CubeSat platforms. This paper reviews the state-of-the-art and future developments of CubeSat radar missions for Earth remote sensing and the implications for NASA’s current and future Earth Science program. The key enabling technologies for radio frequency (RF), digital, and antennas are surveyed, as well as the evolution of the CubeSat avionics, in the aspects that mostly impact radar development, namely power, volume, and attitude control and knowledge and precision orbit determination (POD). We investigate various radar applications that could benefit from low-cost CubeSat platforms, such as altimetry, sounding, precipitation profiling, scatterometry, synthetic aperture radar (SAR), and interferometric SAR (InSAR). We also explore the science motivation and impact of future missions that are based on these technological advancements.

The optimal design of pulse compression waveform/filter pairs for use with near-nadir spaceborne radar in low earth orbit for the observation of clouds and precipitation is discussed. An optimization technique is introduced that considers performance metrics specific to the remote sensing of clouds and precipitation from such platforms. Specifically, the sensitivity of the radar to precipitation and clouds is maximized as close to the ground as required. The sensitivity of the radar near the surface is typically limited by the pulse compression range sidelobes from the surface's echo. Optimization of the waveform/filter pair's performance is facilitated by a time-domain radar scattering model to simulate radar reflectivity range profiles. The presented radar-scattering model accounts for the radar's configuration constraints and platform motion, as well as the spatial distribution and relative motion of the scatterers. In this paper, the optimization of both linear frequency modulation (LFM) and nonlinear frequency modulation (NLFM) waveforms is considered. It is demonstrated that the LFM waveforms provide superior performance over NLFM waveforms for application subject to unmitigated Doppler shifts.

The 2007 Decadal Survey for the National Aeronautics and Space Administration recommended an Aerosol/Cloud/Ecosystems (ACE) mission with a new advanced cloud profiling radar. In this letter, we describe ACERAD, a radar design that could meet the goals for the ACE mission. ACERAD has 35 GHz (Ka-band) and 94 GHz (W-band) channels. It would scan at Ka-band and be nadir looking at W-band. The scanning antenna geometry is a classical Dragonian illuminated by a feed array; a reduced-size prototype of the antenna has been successfully fabricated and tested. ACERAD also uses a quasi-optical transmission line at W-band for low-loss routing of the signal from the transmitter to the antenna and from the antenna to the receiver. This letter briefly describes the ACERAD instrument design and test results for some of the major technologies needed for ACERAD implementation.

Measurement of the Doppler velocity of distributed targets, such as precipitation and rough surfaces, from space is challenging due to the large platform velocity, the broad Doppler spectrum, and the resulting decorrelation between pulses. A previous paper by Durden et al. suggested the use of the displaced phase center antenna (DPCA) technique for the Doppler measurements of such targets. The proposed technique uses two antennas with appropriately chosen pulse timing to cancel platform motion. While DPCA has been used for many years in canceling clutter for point target motion measurements, its use in measuring Doppler from distributed targets was not well established. Here, the authors provide an example of surface measurements from a dual-antenna airborne system and a first demonstration of the use of DPCA to estimate the surface Doppler.

Numerical climate and weather models depend on measurements from space-borne satellites to complete model validation and improvements. Precipitation profiling capabilities are currently limited to a few instruments deployed in Low Earth Orbit (LEO), which cannot provide the temporal resolution necessary to observe the evolution of short time-scale weather phenomena and improve numerical weather prediction models. A constellation of precipitation profiling instruments in LEO would provide this essential capability, but the cost and timeframe of typical satellite platforms and instruments make this solution prohibitive. A new radar instrument architecture that is compatible with low-cost satellite platforms, such as CubeSats and SmallSats, has been designed at JPL that enables constellation missions, which could revolutionize climate science and weather forecasting.

A comparison of model predictions with measurements of near-nadir normalized radar cross sections (NRCSs) of the sea surface at Ku- and Ka-bands is reported. Measurements of Airborne Precipitation Radar Second Generation (APR-2) from near nadir to 25°incidence angle, along with simultaneous wind truth from dropsonde observations, are compared with predictions of the “cutoff-invariant” two-scale model of sea scattering with the overall goal of assessing the model for possible future use in the APR-2 calibration process. The performance of the model as a function of wind speed and incidence angle is therefore emphasized. The measured data set, acquired primarily during the 2010 “Genesis and Rapid Intensification Processes” (GRIP) experiment, includes wind speeds from approximately 5 to 45 m/s. Model comparisons are limited by uncertainties in the wind fields due to limited dropsonde coverage; the data set is separated into “more reliable” (containing wind speeds of 5-20 m/s) and “less reliable” (wind speeds of 5-45 m/s) wind truth categories accordingly. Because a model of the sea spectrum is required for cutoff-invariant model predictions, comparisons with measured data are performed for three differing sea spectrum descriptions. It is found that a bias of less than ~ 1 dB over the wind speed range 5-40 m/s and a standard deviation less than 1 dB over the wind speed range 10-40 m/s can be achieved when using the “unified” sea spectrum description of Elfouhaily The model also provides error levels that are near uniform with respect to both incidence angle and wind speed.

This paper presents a method for filtering the random noise that affects spaceborne Doppler measurements of atmospheric velocities. The proposed method hinges on adaptive low-pass filters that apply to the measured pulse-pair correlation function. The parameters of the filters are found by optimizing the statistics of the velocity residue of the filter. The method is illustrated by simulations of the cloud-profiling radar of the future Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) mission of the European Space Agency and the Japanese Space Exploration Agency. These simulations, which do not include strong convection, show the higher performance of the filters when compared with the traditional increase of the along-track integration length. The results obtained with the filters show that velocity accuracies of 0.48, 0.42, and 0.39 m · s-1are achievable at PRF = {6.1, 7, 7.5} kHz, respectively, while preserving the initial 500-m sampling of the measured EarthCARE data. These results also show the potential benefits of avoiding excessive alongtrack integration, for postprocessing tasks such as dealiasing or the retrieval of the vertical distribution of the atmospheric velocity (e.g., longer than 5 km for cases consistent with the climatologies represented in this data set).

This paper describes the expected performance of the Doppler cloud profiling radar being built for the Earth Cloud Aerosols Radiation Explorer (EarthCARE) mission of the Japanese Aerospace Exploration Agency and the European Space Agency. Spaceborne Doppler radar data are simulated starting from high-resolution Doppler measurements provided by ground-based and airborne Doppler radars, ranging from nonconvective to moderately convective scenarios. The method hinges upon spatial and spectral resampling to consider the specificities of the spaceborne configuration. An error analysis of the resulting Doppler product is conducted to address aliasing and nonuniform beam-filling (NUBF) problems. A perturbation analysis is applied to explore the latter problem and allow for a self-standing systematic correction of NUBF using merely the received reflectivity factor and mean Doppler velocities as measured by the instrument. The results of our simulations show that, at a horizontal integration of 1 km, after proper de-aliasing and NUBF correction, the radar will typically yield a velocity accuracy in the order of 1.3 m·s-1over intertropical regions where the pulse-repetition frequency (PRF)=6.1 kHz, of 0.8 m·s-1where the cloud-profiling radar (CPR) operates at PRF=7 kHz, and, of 0.7 m·s-1over high latitudes where the CPR of EarthCARE will operate at PRF=7.5 kHz.

We analyzed different models to estimate absorption at W-band by gaseous species by taking advantage of the collocated CloudSat-Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. We used the power backscattered by the surface in the green visible wavelength of the lidar of CALIPSO as a reference to infer CloudSat's 94-GHz ocean surface backscatter in clear air and infer the attenuation introduced by gaseous absorption. Different millimeter-wave propagation models (MPMs) and different sources to determine the profile of atmospheric thermodynamic state are used to estimate CloudSat attenuation. These estimates are compared to the observations to calculate the residual dispersion. We show here that we need to adjust the empirical constants of preexisting water vapor absorption models to minimize the dispersion. Our results indicate an overestimation of absorption by the water vapor continuum at 94 GHz in Liebe-based MPM. We also propose a new empirical model to better represent the absorption of the water vapor continuum near 94 GHz. When this model is used in combination with the Advanced Microwave Scanning Radiometer for the Earth Observing System water vapor path and the Global Modeling and Assimilation Office water vapor vertical profile distribution, it leads to the lowest dispersion of the data on a statistical basis (global data over one month). The improved model is expected to optimize water vapor correction applied to CloudSat data and, potentially, also to improve interpretation of brightness temperature measurements in the W-band (e.g., 85- and 98-GHz radiometric channels).

The high correlation of the rain-free surface cross sections at two frequencies suggests that the estimate of differential path-integrated attenuation caused by precipitation along the radar beam can be obtained to a higher degree of accuracy than the path attenuation at either frequency. We explore this potential first analytically and then by examining data from the JPL dual-frequency airborne radar using measurements from the Tropical Composition, Cloud, and Climate Coupling experiment obtained during July-August 2007. Despite an improvement in the accuracy of the differential path attenuation, solving for parameters of the particle size distribution often requires not only this quantity but the single-wavelength path attenuation as well. We investigate a simple method of estimating the single-frequency path attenuation from the differential attenuation and compare this estimate with that derived directly from the surface return.

The authors examine the characteristics of the W-band surface backscatter cross section using data from the 94-GHz cloud profiling radar on the CloudSat mission. These data from CloudSat represent the first global measurements of surface properties at 94 GHz. The authors use these data to investigate seasonal changes in surface backscatter over both land and ocean. The authors also make use of a limited set of off-nadir data to investigate behavior of W-band backscatter from the ocean versus wind speed for incidence angles up to 17°.

Multiple scattering (MS) strongly affects CloudSat's W-band cloud-profiling radar (CPR) reflectivity when the satellite is overpassing moderate and heavy precipitation systems. With the upcoming deployment of W-band Doppler radars in space-Earth Clouds, Aerosols, and Radiation Explorer's CPR in primis-and the goal of retrieving vertical motions within convective systems, there is an urgent need to assess the impact of MS onto the Doppler signatures. A Monte Carlo code capable of simulating the reflectivity enhancement due to higher orders of scattering has been extended to include the Doppler effects. This paper presents the main guidelines for the inclusion of the Doppler analysis into the Monte Carlo scheme. To our knowledge, this simulator is the first one capable of simulating realistic Doppler signals in the presence of MS. The case studies are first presented in uniform beam-filling conditions for the profiles extracted from a cloud-resolving model simulation of deep convection (i.e., 1-D profiles are used to characterize a stratified atmosphere). The simulations demonstrate that, at ranges where MS contributions affect the overall radar signal, two main features appear as the following: 1) The Doppler spectrum tends to broaden with increasing MS enhancement, adding up to the single-scattering (SS) Doppler fading due to the satellite motion; and 2) the mean Doppler of the backscattered signal departs from the mean Doppler determined by the combined effect of the vertical-wind and hydrometeor-terminal velocities at all range bins below the altitude where the MS contribution significantly overcomes the SS. The simulator can be run in nonuniform-beam-filling conditions as well (i.e., a 3-D field is used to characterize the atmosphere at scales smaller than the radar resolution). With its cutting-edge capabilities, it provides a unique tool for the evaluation of the performances of the upcoming high-frequency spaceborne Doppler radars.

The Global Precipitation Measurement mission (GPM) will carry the first dual-frequency spaceborne radar (DPR) for rainfall observation. We use dual-frequency airborne radar data to simulate observations at GPM DPR resolution and frequencies and to investigate errors due to nonuniform beam filling effects. Errors at Ku-band are similar to those found in previous studies. Errors in the Ka-band path-integrated attenuation and near-surface reflectivity are larger than at Ku-band. Errors in rain-top reflectivity, where attenuation is neglected, are smaller at Ka-band than at Ku-band because the Ka-band$Z$–$R$relation is closer to being linear.

The Cloud Profiling Radar, the sole science instrument of the CloudSat Mission, is a 94-GHz nadir-looking radar that measures the power backscattered by hydrometeors (clouds and precipitation) as a function of distance from the radar. This instrument has been acquiring global time series of vertical cloud structures since June 2, 2006. In this paper, an overview of the radar performance and status, to date, is provided together with a description of the basic data products and the surface clutter rejection algorithm introduced for the Release 04 data product release.

The Cloud Profiling Radar (CPR), the primary science instrument of the CloudSat Mission, is a 94-GHz nadir- looking radar that measures the power backscattered by clouds as a function of distance from the radar. This instrument has been acquiring global time series of vertical cloud structure at 500-m vertical resolution and 1.4-km horizontal resolution since June 2, 2006. In this paper an overview of the radar performance during the first year in flight is provided.

We propose the use of multiantenna radars for precipitation measurement from moving platforms. The primary motivation is measurement of vertical motion from spaceborne radars. Preliminary analysis of the concept and application to a specific example indicate that such a system would be feasible

The cloud profiling radar (CPR), the primary science instrument of the CloudSat Mission, is a 94-GHz nadir- looking radar that measures the power backscattered by clouds as a function of distance from the radar. This instrument will acquire a global time series of vertical cloud structure at 500-m vertical resolution and 1.4-km horizontal resolution. CPR will operate in a short-pulse mode and will yield measurements at a minimum detectable sensitivity of -28 dBZ.

Multiple scattering effects from spherical water particles of uniform diameter are studied for a W-band pulsed radar. The Gaussian transverse beam-profile and the rectangular pulse- duration are used for calculation. An second-order analytical solution is derived for a single layer structure, based on a time- dependent radiative transfer theory. When the range resolution is fixed, increase in footprint radius leads to increase in the second order reflectivity that is defined as the ratio of the second order return to the first order one. This undesirable feature becomes more serious as the range increases. Since the spaceborne millimeter-wavelength radar has a large footprint radius that is competitive to the mean free path, the multiple scattering effect must be taken into account for analysis.

The dual-frequency Airborne Precipitation Radar-2 (APR-2) was deployed during the Wakasa Bay Experiment in 2003, for validation of the Advanced Microwave Scanning Radiometer-EOS. Besides providing extensive observations of diverse precipitating systems, this Ku-(13.4 GHz) and Ka-band (35.6 GHz) cross-track scanning radar measured sea surface backscatter simultaneously. While the characteristics of the normalized sea surface cross section sigma0at Ku-band are well understood and widely published, the existing experimental data concerning sigma0at Ka-band are scarce and results are inconsistent. In this letter, the Ku/Ka-band sigma0measurements collected by APR-2, together with the estimated uncertainties, are discussed. In general, the measured sigma0at Ka-band at around 10deg incidence angle appears to be close to that at Ku-band sigma0, and Ka-band exhibits a nonnegligible difference in wind dependence with respect to Ku-band for moderate to high winds

This study analyzes passive and active microwave measurements during the 2003 Wakasa Bay field experiment for understanding of the electromagnetic characteristics of frozen hydrometeors at millimeter-wave frequencies. Based on these understandings, parameterizations of the electromagnetic scattering properties of snow at millimeter-wave frequencies are developed and applied to the hydrometeor profiles obtained by airborne radar measurements. Calculated brightness temperatures and radar reflectivity are compared with the millimeter-wave measurements.

In this paper, we expand the previous theory to be applied to a generic drop size distribution with spheroidal raindrops including spherical raindrops. Results will be used to discuss the multiple scattering effects on the backscatter measurements acquired by a W-band nadir-pointing radar.

Snowfall is an important component of the Earth's precipitation and hydrological cycle. Remote measurements of frozen hydrometeor properties have been limited because coincident measurements of microphysical and electromagnetic properties of snowfall have not been available. Snowfall measurement from space has been suggested as a solution to overcome this limitation. The precipitating clouds contain a sufficient density of ice water equivalent from snow crystals, graupel, or both, when brightness temperature is at 85 GHz. The NOAA Advanced Microwave Sounding Unit (AMSU) has been used to derive snowfall over land using millimeter-wave radiometry. This study analyzes the millimeter-wave radiometric measurements of frozen hydrometeors during the field experiment that was held in Wakasa bay of Japan in January 29, 2003. It was found that a lognormal distribution represents the snow PSD during the field experiments. The MM5 cloud simulation is employed to provide temperature and humidity profiles for the radiative transfer calculations. This study seeks to derive characteristics of snow whose electromagnetic properties are consistent with microwave brightness temperature at several frequencies provided by the MIR sensors and the radar reflectivity measured by PR-2 (Precipitation Radar) and ACR (Airborne Cloud Radar).

Radar data obtained through the NASA/JPL Airborne Precipitation Radar APR-2 during the Wakasa Bay Experiment in January/February 2003 were processed to obtain calibrated reflectivity measurements, rainfall/snowfall velocity measurements, classification of the surface type and detection of the boundaries of the melting layer of precipitation. In this paper the processing approach is described together with an overview of the resulting data quality and known issues

The current Geostationary Operational Environmental Satellites (GOES) are eqipped to make cloud top measurements only. In contrast, a millimeter-wave radar allows 3-D measurements of precipitation associated with hurricanes and other convective systems. It also provides important inputs for numerical weather prediction models for improving the accuracy of weather nowcasting and forecasting.

Abstract- In this paper we will present the results of the trade studies on the performances of a spacebome Doppler radar in measuring vertical rainfall velocity. Particular emphases will be placed on: 1) the choice of the PRF vs. antenna size ratio, 2) the choice of the observational strategy, 3) the choice of the operating frequency; and the 4) processing strategy. The results show that accuracies of 1 m/s or better can be achieved with the currently available technology and with careful selection the system parameters. 1.

The authors describe a differential method for estimating mean concentrations of atmospheric molecular components along a quasivertical rectilinear Earth-air path utilizing a transmitter-receiver pair operating at infrared. The choice of a differential method is due to the need to limit calibration problems without utilizing more complex and costly systems such as DIAL, whose capabilities are definitely oversized for this kind of measurement. For this objective, a preliminary selection of the optimal wavenumbers for each molecular species of interest is needed. This is the main issue discussed in this paper, after which the analysis focuses on the effects of the uncertainties on atmospheric parameters that need to be estimated to provide the final mean-concentration estimates. The feasibility study is carried out on carbon monoxide, considered as test species of interest in the reported simulations of atmospheric propagation, based on standard atmospheric models. Technological requirements are finally discussed.

The authors address the problem of estimating vertical profiles of atmospheric water vapor by means of attenuation measurements simultaneously made at different frequencies along a vertical satellite-ground link. The operating frequencies selected are those around the spectral absorption lines of water vapor at 22.235 GHz. A simulation is presented of multifrequency attenuation measurements, based on an atmospheric propagation model and on radiosonde data providing true profiles of temperature, pressure, and water vapor. The results indicate that such multifrequency measurements are correlated to variations of the vertical profiles of water vapor. It is therefore expected that vertical detail of such profiles depends on number and position of the frequencies utilized.

In this paper, we analyze the feasibility and performance of a particular tomographic system for atmospheric pollution monitoring over limited areas (e.g., urban areas). Such a system exploits attenuation-based infrared measurements of the average concentration of the fundamental molecular species of pollutants along rectilinear paths. First, the paper demonstrates the feasibility of an apparatus based on semiconductor infrared laser diode transmitters and passive retroreflectors, capable of measuring the average concentration of pollutants along rectilinear paths with 2-km maximum length, by exploiting their infrared absorption properties. For each gaseous species of interest, the optimal wavelength is then singled out, with the purpose of applying the derivative method for measuring the corresponding average atmospheric concentration. The optimal wavelengths are determined based on both absorption data of atmospheric components and plausible ranges of variation of their concentration. Finally, we present simulations carried out to evaluate the reconstruction of spatial-concentration fields of several air pollutants obtained through a tomographic-inversion algorithm exploiting simultaneous attenuation measurements made along different infrared links. Two different network topologies for such measurements are considered.

The authors analyze the feasibility and performance of a particular tomographic system for atmospheric pollution monitoring over limited areas (e.g. urban areas). Such a system exploits attenuation-based infrared measurements of the average concentration of the fundamental molecular species of pollutants along rectilinear paths. First, the paper demonstrates the feasibility of an apparatus based on semiconductor infrared laser diode transmitters and passive retroreflectors, capable of measuring the average concentration of pollutants along rectilinear paths with 2 km maximum length, by exploiting their infrared absorption properties. For each gaseous species of interest, the optimal wavelength is then singled out, with the purpose of applying the derivative method for measuring the corresponding average atmospheric concentration. The optimal wavelengths are determined based on both absorption data of atmospheric components and plausible ranges of variation of their concentration. Finally, the authors present simulations carried out to evaluate the reconstruction of spatial concentration fields of several air pollutants, obtained through a tomographic inversion algorithm exploiting simultaneous attenuation measurements made along different infrared links. Two different network topologies for such measurements are considered.

The microwave tomographic inversion technique (MTIT) proposed in 1991 for reconstruction of rainfall fields at ground through microwave attenuation measurements is reconsidered. A new algorithm for data inversion is presented [referred to as stochastic reconstruction technique (SRT)] that generally performs better than the one originally adopted [referred to as arithmetic reconstruction technique (ART)]. Improvement is achieved in spatial definition and general reliability of rainfall field reconstruction. The new model adopted to represent the reconstructed rainfall fields leads to a completely different strategy for the inversion problem, and this strategy is based on a global optimization stochastic technique (GOST). Results obtained through the SRT-MTIT are presented in the paper and compared to those obtained by employing the ART-MTIT. It also is shown that, based on the SRT-MTIT approach, fast and reliable time tracking of rainfall events is made possible by exploiting previous reconstructions and by the improved long-term physical consistency of the model adopted for rainfall field decomposition.