Radar Calibration Research Articles

An Investigation of the Process Stability of RF SiP Made of DuPont 943 and 9K7

RF packaging is one of the most challenging but also the fastest growing topic in low temperature cofired ceramic (LTCC) technology. Today LTCC is particularly useful for advanced packages and systems-in-package because of its electrical, functional, and thermomechanical properties as well as its excellent long-term stability and reliability. LTCC combines the potential for miniaturization and low loss handling of high frequencies up to 110 GHz and it also offers the opportunity to integrate additional features. Therefore it has to go through various manufacturing steps and several refirings without any performance degradation or loss of dimensional accuracy. This article discusses the impact of thermal postprocessing on RF characteristics and geometric properties of LTCC. Ceramic substrates with radar front ends, calibration structures, and other test vehicles made of DuPont Green Tape® 943 and 9K7 were cofired following the recommended conditions and refired several times in order to investigate and compare the influence of the postfiring. The flatness, dimensions, and RF performance of the ceramics up to 110 GHz were evaluated and compared.

Special Sensor Microwave Imager (SSM/I) Intersensor Calibration Using a Simultaneous Conical Overpass Technique

AbstractA new intersensor calibration scheme is developed for the Defense Meteorological Satellite Program Special Sensor Microwave Imager (SSM/I) to correct its scan-angle-dependent bias, the radar calibration beacon interference on the F-15 satellite, and other intersensor biases. The intersensor bias is characterized by the simultaneous overpass measurements with the F-13 SSM/I as a reference. This sensor data record (SDR) intersensor calibration procedure is routinely running at the National Oceanic and Atmospheric Administration and is now used for reprocessing all SSM/I environmental data records (EDR), including total precipitable water (TPW) and surface precipitation. Results show that this scheme improves the consistency of the monthly SDR’s time series from different SSM/I sensors. Relative to the matched rain products from the Tropical Rainfall Measuring Mission, the bias of SSM/I monthly precipitation is reduced by 12% after intersensor calibration. TPW biases between sensors are reduced by 75% over the global ocean and 20% over the tropical ocean, respectively. The intersensor calibration reduces biases by 20.6%, 15.7%, and 6.5% for oceanic, land, and global precipitation, respectively. The TPW climate trend is 1.59% decade−1 (or 0.34 mm decade−1) for the global ocean and 1.39% decade−1 (or 0.63 mm decade−1) for the tropical ocean, indicating related trends decrease of 38% and 54%, respectively, from the uncalibrated SDRs. Results demonstrate the large impacts of this calibration on the TPW climate trend.

CALIBRATION OF SPACEBORNE LINEARLY POLARIZED LOW FREQUENCY SAR USING POLARIMETRIC SELECTIVE RADAR CALIBRATORS

Spaceborne synthetic aperture radar (SAR) systems operating at lower frequencies, such as P-band, are signiflcantly afiected by Faraday rotation (FR) efiects. This paper presents a novel algorithm for measuring system errors (channel imbalance and cross-talk) in the presence of Faraday rotation for spaceborne polarimetric SAR data. It uses four polarimetric selective calibrators (four polarimetric active radar calibrators (PARCs) or possibly two PARCs and two gridded trihedrals). Theoretical analysis and simulations demonstrate that the optimized calibration scheme puts tight constraints on the accuracy of the associated Faraday rotation if the cross-talk is to be accurately measured. There are also strong constraints on the allowable signal-to-noise ratio and average polarimetric noise associated with the calibration devices. The analysis suggests that, unless the calibration sites are at the magnetic equator, independent measurements of total electron content (TEC) from a direct ground-satellite line-of-sight dual-frequency system are also needed.

External calibration of a polarimetric synthetic-aperture radar for a limited number of types of reference reflectors

Capabilities of the external calibration of a polarimetric synthetic-aperture radar (SAR) and the monitoring of the radar parameters under flight conditions for a limited number of types of reference calibration targets are determined. An analytic form of the algorithm for neutralization of SAR hardware distortions in the measurement of the scattering matrix of the observed object is proposed and possibilities for application of this algorithm under the conditions of unrealizable total polarimetric calibration are analyzed. The possibilities of determining the particular calibration parameters and their combinations with the use of one or two reference reflectors are analyzed. It is shown that, in the measurement of the scattering matrix of a reciprocal object, it is sufficient to use two types of reference reflectors.

Lake Surface Height Calibration of Jason-1 and Jason-2 Over the Great Lakes

This study presents results of Jason-1 (J1) and Jason-2 (J2) radar altimetry absolute calibration (cal/val) over the Marblehead lake water level gauge, with an aid of a GPS buoy, in Lake Erie, the Great Lakes, in North America. The altimeter bias is estimated using the height difference between the altimeter lake surface height and the in situ data in each altimeter 10-day repeat cycle. The altimeter bias estimates for J1 are 81 ± 2 and 70 ± 2 mm for Geophysical Data Record (GDR) Versions ‘B’ and ‘C’, respectively, and 148 ± 5 mm (GDR) and 147 ± 7 mm (IGDR) for J2, respectively. The bias estimates are slightly smaller compared with estimates at other dedicated calibration sites such as the Harvest Platform, the Corsica Site, and the Bass Strait site due in part to the effect of the sea state bias. The J2-to-J1 relative bias determined in the tandem mode over Lake Erie is 84 ± 28 mm, which agrees well with the results from the global analysis and the dedicated sites aforementioned.

Cosmic radio noise observations using a mid-latitude meteor radar

For the investigation of meteoroid properties the measurement of the electron line density in meteor ambipolar plasma trails is an important parameter, which becomes accessible by a radar calibration. Radars operating in the frequency range between 20 and 50 MHz are also sensitive to extraterrestrial radio waves. Depending on the geographic position and beam tilt each system observes a characteristic pattern of cosmic emissions, which can be considered to be Gaussian noise. This work demonstrates the possibilities to perform a radar calibration for standard commercial all-sky meteor radars using a delay line method and a calibrated noise source. Additionally, we also used the cosmic noise sources to estimate the impact of the antenna pattern and potential losses of the hardware (e.g. cables, connectors). The calibrated radio noise measurements are compared to a reference by mapping the Collm radar beam pattern on a sky noise maps available in the literature.

Performance evaluation of high-resolution rainfall estimation by X-band dual-polarization radar for flash flood applications in mountainous basins

Different relations between surface rainfall rate, R , and high-resolution polarimetric X-band radar observations were evaluated using a dense network of rain gauge measurements over complex terrain in Central Italian Alps. The specific differential phase shift, K DP , rainfall algorithm ( R KDP ) although associated with low systematic error it exhibits low sensitivity to the spatial variability of rainfall as compared to the standard algorithm ( R STD ) that is based on the reflectivity-to-rainfall ( Z – R ) relationship. On the other hand, the dependence of the reflectivity measurement on the absolute radar calibration and the rain-path radar signal attenuation introduces significant systematic error on the R STD rainfall estimates. The study shows that adjusting the Z – R relationship for mean-field bias determined using the R KDP estimates as reference is the best technique for acquiring unbiased radar-rainfall estimates at fine space–time scales. Overall, the bias of the R KDP -adjusted Z – R estimator is shown to be lower than 10% for both storm cases, while the relative root-mean-square error is shown to range from 0.6 (convective storm) to 0.9 (stratiform storm). A vertical rainfall profile correction (VPR) technique is tested in this study for the stratiform storm case. The method is based on a newly developed VPR algorithm that uses the X-band polarimetric information to identify the properties of the melting layer and devices a precipitation profile that varies for each radar volume scan to correct the radar-rainfall estimates. Overall, when accounting for the VPR effect there is up to 70% reduction in the systematic error of the 3° elevation estimates, while the reduction in terms of relative root-mean-square error is limited to within 10%.

Calibration of Local Area Weather Radar—Identifying significant factors affecting the calibration

A Local Area Weather Radar (LAWR) is an X-band weather radar developed to meet the needs of high resolution rainfall data for hydrological applications. The LAWR system and data processing methods are reviewed in the first part of this paper, while the second part of the paper focuses on calibration. The data processing for handling the partial beam filling issue was found to be essential to the calibration. LAWR uses a different calibration process compared to conventional weather radars, which use a power-law relationship between reflectivity and rainfall rate. Instead LAWR uses a linear relationship of reflectivity and rainfall rate as result of the log transformation carried out by the logarithmic receiver as opposed to the linear receiver of conventional weather radars. Based on rain gauge data for a five month period from a dense network of nine gauges within a 500 × 500 m area and data from a nearby LAWR, the existing calibration method was tested and two new methods were developed. The three calibration methods were verified with three external gauges placed in different locations. It can be concluded that the LAWR calibration uncertainties can be reduced by 50% in two out of three cases when the calibration is based on a factorized 3 parameter linear model instead of a single parameter linear model.

An approach to combine radar and gauge based rainfall data under consideration of their qualities in low mountain ranges of Saxony

Abstract. An approach to combine gauge and radar data and additional quality information is presented. The development was focused on the improvement of the diagnostic for temporal (one hour) and spatial (1×1 km2) highly resolved precipitation data. The method is embedded in an online tool and was applied to the target area Saxony, Germany. The aim of the tool is to provide accurate spatial rainfall estimates. The results can be used for rainfall run-off modelling, e.g. in a flood management system. Quality information allows a better assessment of the input data and the resulting precipitation field. They are stored in corresponding fields and represent the static and dynamic uncertainties of radar and gauge data. Objective combination of various precipitation and quality fields is realised using a cost function. The findings of cross validation reveal that the proposed combination method merged the benefits and disadvantages of interpolated gauge and radar data and leads to mean estimates. The sampling point validation implies that the presented method slightly overestimated the areal rain as well as the high rain intensities in case of convective and advective events, while the results of pure interpolation method performed better. In general, the use of presented cost function avoids false rainfall amount in areas of low input data quality and improves the reliability in areas of high data quality. It is obvious that the combined product includes the small-scale variability of radar, which is seen as the important benefit of the presented combination approach. Local improvements of the final rain field are possible due to consideration of gauges that were not used for radar calibration, e.g. in topographic distinct regions.

The TAMORA algorithm: satellite rainfall estimates over West Africa using multi-spectral SEVIRI data

Abstract. A multi-spectral rainfall estimation algorithm has been developed for the Sahel region of West Africa with the purpose of producing accumulated rainfall estimates for drought monitoring and food security. Radar data were used to calibrate multi-channel SEVIRI data from MSG, and a probability of rainfall at several different rain-rates was established for each combination of SEVIRI radiances. Radar calibrations from both Europe (the SatPrecip algorithm) and Niger (TAMORA algorithm) were used. 10 day estimates were accumulated from SatPrecip and TAMORA and compared with kriged gauge data and TAMSAT satellite rainfall estimates over West Africa. SatPrecip was found to produce large overestimates for the region, probably because of its non-local calibration. TAMORA was negatively biased for areas of West Africa with relatively high rainfall, but its skill was comparable to TAMSAT for the low-rainfall region climatologically similar to its calibration area around Niamey. These results confirm the high importance of local calibration for satellite-derived rainfall estimates. As TAMORA shows no improvement in skill over TAMSAT for dekadal estimates, the extra cloud-microphysical information provided by multi-spectral data may not be useful in determining rainfall accumulations at a ten day timescale. Work is ongoing to determine whether it shows improved accuracy at shorter timescales.

Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

Abstract. This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m) and temporal (16 s) resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with non-polarimetric X-band radar over flat terrain. An appropriate radar reflectivity – rain rate relation is derived from measurements of raindrop size distributions and compared with radar – rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

Parameter estimation of state space models for univariate observations

This paper contributes to the problem of estimation of state space model parameters by proposing estimators for the mean, the autoregressive parameters and the noise variances which, contrarily to maximum likelihood, may be calculated without assuming any specific distribution for the errors. The estimators suggested widen the scope of the application of the generalized method of moments to some heteroscedastic models, as in the case of state-space models with varying coefficients, and give sufficient conditions for their consistency. The paper includes a simulation study comparing the proposed estimators with maximum likelihood estimators. Finally, these methods are applied to the calibration of the meteorological radar and estimation of area rainfall.

Geosensing systems engineering for ocean security and sustainable coastal zone management

Three major threats to ocean security and coastal zone sustainability - global warming, the loss of ocean biodiversity, and pollution - are combining to threaten the ecological integrity of our marine environment and life support systems. We put forward a geomatics-based systems engineering architecture to identify the location and extent of oil spills, thereby improving the ecological integrity of the world’s oceans and helping contingency planners to determine required assets, personnel and other resources. This real-time, event-based and cost effective emergency management decision support system can aid in the classification, detection, and monitoring of oil spills in the marine environment. The developed Synthetic-Aperture Radar (SAR) processing and calibration techniques efficiently monitor environmental changes in inaccessible ocean regions, characterize oil spill scenarios, and help to identify spill sources. The system is used to improve emergency management in the Gulf of Mexico, with application to oil spills arising from Hurricane Katrina.

Radar/rain‐gauge comparisons on squall lines in Niamey, Niger for the AMMA

AbstractMassachusetts Institute of Technology C‐band radar observations are integrated with rainfall measurements from an extensive network of gauges in Niamey, Niger, West Africa, for the African Monsoon and Multidisciplinary Analysis (AMMA). The large number of gauges available enabled Ze–R power‐law relationships for the convective and stratiform regions of individual squall lines. The Ze–R relationships based solely on radar measurements directly over the gauges were developed for the estimate of rainfall and attendant latent heat release (by other AMMA investigators) where gauges were unavailable. The low prefactor values of the Ze–R power laws relative to like values for Z–R disdrometer power laws have contributions of order 1–2 dB from the use of the lowest beam tilt (0.57° ) and ∼1–2 dB by the radar reading low. (The sphere calibration and the Tropical Rainfall Measuring Mission TRMM—radar calibration are inconsistent at the 1–2 dB level for unknown reasons.) Radar/gauge comparisons are also shown for individual storms. Accurate, unbiased results for the convective regime require adjustment of the radar‐to‐gauge radials for attenuation. Beam filling problems and aliasing issues can often be identified in the case of outlier points. Copyright © 2010 Royal Meteorological Society

Polarimetric SAR Internal Calibration Scheme Based on T/R Module Orthogonal Phase Coding

Two important aspects of internal calibration of polarimetric synthetic aperture radar (SAR) are discussed, i.e., individual transmit/receive module (TRM) calibration and system gain calibration. The system has a general structure utilizing a phased array antenna composed of dual-channel TRMs. TRM gain and phase calibration is carried out using orthogonal phase coding (OPC). The signal of the individual TRM is phase-encoded according to a set of orthogonal codes to be separated from the composite calibration signal. OPC uses 1 bit of a digital phase-shifter for encoding, without the need for additional encoding hardware. Performance of the method is examined. Calibration results are developed both theoretically and through simulation in case of TRM amplifier or phase-shifter failure. Zero-padding is used to eliminate calibration error of the first TRM. A crosstalk model is proposed to investigate the effect of imperfect isolation between the two polarization channels of each TRM, and a way to reduce this error is also given. At last, system path gain variation is measured utilizing the internal calibration loop. The OPC method has an accuracy of 0.2 dB for gain and better than 2deg for phase, with 10-dB signal-to-noise ratio and perfect isolation between the two polarization channels. The error due to imperfect isolation is usually small and can be ignored. The simple way to detect TRM malfunction is verified through simulation, and it is also in accordance with TerraSAR-X in-orbit calibration outcomes. The proposed OPC method is shown to be an effective way of internally calibrating TRMs of a phased array antenna.

Difficulties with Correcting Radar Rainfall Estimates Based on Rain Gauge Data: A Case Study of Severe Weather in Montana on 16–17 June 2007

Abstract The principal source of information for operational flash flood monitoring and warning issuance is weather radar–based quantitative estimates of precipitation. Rain gauges are considered truth for the purposes of validating and calibrating real-time radar-derived precipitation data, both in a real-time sense and climatologically. This paper examines various uncertainties and challenges involved with using radar and rain gauge data in a severe local storm environment. A series of severe thunderstorm systems that occurred across northeastern Montana illustrates various problems with comparing radar precipitation estimates and real-time gauge data, including extreme wind effects, hail, missing gauge data, and radar quality control. Ten radar–gauge time series pairs were analyzed with most found to be not useful for real-time radar calibration. These issues must be carefully considered within the context of ongoing efforts to develop robust real-time tools for evaluating radar–gauge uncertainties. Recommendations are made for radar and gauge data quality control efforts that would benefit the operational use of gauge data.

Assessment of Cloudsat Reflectivity Measurements and Ice Cloud Properties Using Ground-Based and Airborne Cloud Radar Observations

Abstract A quantitative assessment of Cloudsat reflectivities and basic ice cloud properties (cloud base, top, and thickness) is conducted in the present study from both airborne and ground-based observations. Airborne observations allow direct comparisons on a limited number of ocean backscatter and cloud samples, whereas the ground-based observations allow statistical comparisons on much longer time series but with some additional assumptions. Direct comparisons of the ocean backscatter and ice cloud reflectivities measured by an airborne cloud radar and Cloudsat during two field experiments indicate that, on average, Cloudsat measures ocean backscatter 0.4 dB higher and ice cloud reflectivities 1 dB higher than the airborne cloud radar. Five ground-based sites have also been used for a statistical evaluation of the Cloudsat reflectivities and basic cloud properties. From these comparisons, it is found that the weighted-mean difference ZCloudsat − ZGround ranges from −0.4 to +0.3 dB when a ±1-h time lag around the Cloudsat overpass is considered. Given the fact that the airborne and ground-based radar calibration accuracy is about 1 dB, it is concluded that the reflectivities of the spaceborne, airborne, and ground-based radars agree within the expected calibration uncertainties of the airborne and ground-based radars. This result shows that the Cloudsat radar does achieve the claimed sensitivity of around −29 dBZ. Finally, an evaluation of the tropical “convective ice” profiles measured by Cloudsat has been carried out over the tropical site in Darwin, Australia. It is shown that these profiles can be used statistically down to approximately 9-km height (or 4 km above the melting layer) without attenuation and multiple scattering corrections over Darwin. It is difficult to estimate if this result is applicable to all types of deep convective storms in the tropics. However, this first study suggests that the Cloudsat profiles in convective ice need to be corrected for attenuation by supercooled liquid water and ice aggregates/graupel particles and multiple scattering prior to their quantitative use.

Experimental results on rainfall estimation in complex terrain with a mobile X-band polarimetric weather radar

In this work the capability of reliable rainfall measurements with small weather radars in complex terrain for flood forecasting purposes is examined. Rain measurements were carried out during winter–spring 2007 with a mobile X-band dual-polarization radar in the northwestern mountainous part of the island of Crete in Greece. In this area a 2D-video disdrometer and a network of raingauges was installed for radar calibration and evaluation of rainfall measurements, respectively. The complex terrain of the experimental site may significantly reduce the performance of rain measurements due to ground clutter and partial or total beam blockage. A beam blockage algorithm using high resolution terrain data was applied in order to find areas with significant terrain effects and estimate correction of the radar measurements. Rain attenuation correction was based on modern sophisticated algorithms using differential phase measurements. The accuracy of rainfall estimation from standard or polarimetric algorithms at plan position indicator (PPI) scans was examined for high-temporal resolution (1 min) rainfall rates and accumulated rainfall values for winter and spring time rain events. For high elevation measurements, which were required in order to avoid terrain effects in large areas of interest, a correction for the vertical-profile-of-reflectivity (VPR) was also applied to the radar data. An average VPR model used in the corresponding correction of reflectivity was constructed based on range–height indicator (RHI) scans. It was concluded that quantitative high resolution X-band radar observations of rainfall in complex terrain is possible after careful application of all the above processing steps.

Radar rainfall estimation for the post-event analysis of a Slovenian flash-flood case: application of the Mountain Reference Technique at C-band frequency

Abstract. This article is dedicated to radar rainfall estimation for the post-event analysis of a flash flood that occurred on 18 September 2007 in Slovenia. The utility of the Mountain Reference Technique is demonstrated to quantify rain attenuation effects that affect C-band radar measurements in heavy rain. Maximum path-integrated attenuation between 15 and 20 dB were estimated thanks to mountain returns for path-averaged rain rates between 10 and 15 mm h−1 over a 120-km path. Assuming the reflectivity-attenuation relationship to be known, the proposed technique allows for estimating an effective radar calibration correction factor to be accounted for in the parameterization of the attenuation correction. Screening effects are quantified using a geometrical calculation based on a digitized terrain model of the region. The vertical structure of the reflectivity is modeled with a normalized apparent vertical profile of reflectivity. Implementation of the radar data processing indicates that: (1) the combined correction for radar calibration and attenuation effects allows for obtaining satisfactory radar rain estimates (Nash criterion of 0.8 at the event time scale); (2) due to the attenuation equation instability, it is however compulsory to limit the maximum path-integrated attenuation to be corrected to about 10 dB; (3) the results also prove to be sensitive on the parameterization of reflectivity-attenuation-rainrate relationships.

A Method to Estimate Vertically Integrated Amounts of Cloud Ice and Liquid and Mean Rain Rate in Stratiform Precipitation from Radar and Auxiliary Data

Abstract A method to retrieve total vertical amounts of cloud liquid and ice in stratiform precipitating systems is described. The retrievals use measurements from the vertically pointing Ka- and W-band cloud radars operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and auxiliary measurements from a scanning National Weather Service radar and a ground-based disdrometer. Separation between the cloud liquid and rain is based on estimations of the total attenuation of millimeter-wavelength radar signals in the liquid hydrometeor layer. Disdrometer measurements are used for the retrieval constraints. Because the liquid phase hydrometeor retrievals use only differential measurements, they are immune to the absolute radar calibration uncertainties. Estimates of the ice cloud phase are performed using empirical relations between absolute radar reflectivity and ice water content. Data from the nearby scanning weather-service radar, which operates at a lower frequency, are used to correct cloud radar measurements observed above the freezing level for attenuation caused by the layers of liquid and melting hydrometeors and also by wet radomes of cloud radars. Polarimetric and vertical Doppler measurements from ARM cloud radars provide a distinct separation between regions of liquid and ice phases, and therefore the corresponding retrievals are performed in each region separately. The applicability of the suggested method is illustrated for a stratiform precipitation event observed at the ARM Southern Great Plains facility. Expected uncertainties for retrievals of cloud liquid water path are estimated at about 200–250 g m−2 for typical rainfall rates observed in stratiform systems (∼3–4 mm h−1). These uncertainties increase as rainfall rate increases. The ice water path retrieval uncertainties can be as high as a factor of 2.