Precipitation detection by the TOPEX/Poseidon dual frequency radaraltimeter, TOPEX microwave radiometer, Special Sensor Microwave/Imagerand climatological shipboard reports

The athors evaluate the ability of a dual-frequency radar (C and Ku band) altimeter to detect rain events. A TOPEX/Poseidon (T/P) altimeter rain flag for the year 1994 is compared to collocated rain rate (RR) from the Defense Meteorological Satellite Program's Special Sensor Microwave Imager (DMSP SSM/I), as processed to the TOPEX/Poseidon passive radiometer's (TMR) liquid-water content, and to a 34-year climatology of shipboard present-weather reports compiled by G. W. Petty (1995). The altimeter-SSM/I analysis is couched in terms of the tradeoff between the probability of a false positive and the probability of a failure to detect rain. The authors show that the ability of the SSM/I and TMR datasets to detect precipitation are closer to each other than to either the altimeter or the shipboard climatology, and this difference is accentuated at latitudes poleward of 45°. They argue that the different footprint sizes explain only part of this discrepancy. They propose that the difference at high latitudes is caused by the altimeter data's sensitivity to snow. In order to detect precipitation (as opposed to detecting bad altimetric values or out-of-range altimetric corrections), a TMR-only flag with liquid-water content of 600 μm recovers too few rain events, 400 μm is close to climatological moderate-to heavy intensity rains, and 200 μm is close to rain of any intensity. For the same purpose, a combined altimeter and TMR flag, with a TMR threshold of 100 μm and with the Ku radar cross section 1.5 standard deviations below an average Ku/C curve, gives the best match for climatological precipitation of any intensity class     

Impact of rain on spaceborne Ku-band wind scatterometer data

The accuracy of Ku-band ocean wind scatterometers (i.e., NSCAT and SeaWinds) is impacted to varying degrees by rain. In order to determine how to best flag rain-contaminated wind vector cells and ultimately to calibrate out the effects of rain as much as possible, we must understand the impact of rain on the backscatter measurements that are used to retrieve wind vectors. This study uses collocated SSM/I rain rate measurements, NCEP wind fields, and SeaWinds on QuikSCAT backscatter measurements to empirically fit a simple theoretical model of the effect of rain on /spl sigma//sub 0/, and to check the validity of that model. The chief findings of the study are (1) horizontal polarization measurements are more sensitive to rain than vertical polarization, (2) sensitivity to rain varies dramatically with wind speed, and (3) the additional backscatter due to rain overshadows the rain-related attenuation.     

Development and validation of altimeter wind speed algorithms usingan extended collocated Buoy/Topex dataset

The development and validation of altimeter wind speed algorithms is investigated following the collation of the largest dataset to-date of coincident altimeter/buoy open ocean measurements. Nonlinear relationships between buoy wind and Topex backscatter are fitted to the 4500 points dataset using least-squares (LSQ). The addition of altimeter significant wave height (SWH) information causes a small but significant reduction of about 10% in root-mean-square (rms) error. The new LSQ algorithms yield significant improvement of the global wind speed bias and rms error compared to earlier models, but describe the wind to backscatter relationship poorly at extreme wind speeds. Best results are obtained with the Gourrion et al. (2000) model, improving on the Witter and Chelton (WC91) (1991) model used operationally. A residual dependence on sea state persists in all wind algorithms, which underestimate winds in young sea conditions on average by 1-1.5 m/s. A case study confirms that ordinary LSQ attribute excessive weight to the peak of the wind speed histogram and yield algorithms with poor performance at extreme winds. Measurement errors are shown to greatly influence the fitted models performance, as accounting for normally distributed errors in both altimeter and buoy measurements with orthogonal distance regressions (ODRs) yields significant improvements     

An analysis of SeaWinds-based rain retrieval in severe weather events

The Ku-band SeaWinds scatterometer estimates near-surface ocean wind vectors by relating measured backscatter to a geophysical model function for the near-surface vector wind. The conventional wind retrieval algorithm does not explicitly account for SeaWinds' sensitivity to rain, resulting in rain-caused wind retrieval error. A new retrieval method, termed "simultaneous wind/rain retrieval," that estimates both wind and rain from rain-contaminated measurements has been previously proposed and validated with Tropical Rain Measuring Mission data. Here, the accuracy of rains retrieved by the new method is validated through comparison with the Next Generation Weather Radar (NEXRAD) in coastal storm events. The rains detected by both sensors are comparable, though SeaWinds-estimated rains exhibit greater variability. The performance of simultaneous wind/rain retrieval in flagging excessively rain-contaminated winds is discussed and compared to existing methods. A new rain-only retrieval algorithm for use in rain-backscatter-dominated areas is proposed and tested. A simple noise model for SeaWinds rain estimates is developed, and Monte Carlo simulation is employed to verify the model. The model shows that SeaWinds rain estimates have a standard deviation of 2.5 mm/h, which is higher than the NEXRAD measurements. Thresholding SeaWinds rain estimates at 2 mm/h yields a better rain flag than current rain flag algorithms.     

Prelaunch performance of the NASA altimeter for the TOPEX/Poseidonproject

The TOPEX/Poseidon radar altimeter satellite applies advances in remote sensing instrumentation to reduce long wavelength measurement errors to dramatically lower levels. The TOPEX altimeter measures the range to the ocean surface with 2-cm precision and accuracy through the use of both Ku- and C-band radars, a high pulse repetition frequency, an agile tracker, and absolute internal height calibration. Dual pulse bandwidths for both frequencies make it possible to quickly acquire the surface and begin tracking after crossing the land/ocean boundary. The altimeter requirements and the elements of the altimeter design that have resulted in meeting these requirements are presented. Prelaunch test data, based on the use of a radar altimeter system evaluator to simulate the backscatter from the ocean surface, are presented to demonstrate that the TOPEX altimeter will meet these requirements and provide the data necessary to the understanding of basin scale mean circulation     

Observations of radar backscatter at Ku and C bands in the presenceof large waves during the Surface Wave Dynamics Experiment

Ocean radar backscatter in the presence of large waves is investigated using data acquired with the Jet Propulsion Laboratory NUSCAT radar at Ku band for horizontal and vertical polarizations and the University of Massachusetts C-SCAT radar at C band for vertical polarization during the Surface Wave Dynamics Experiment. Off-nadir backscatter data of ocean surfaces were obtained in the presence of large waves with significant wave height up to 5.6 m. In moderate-wind cases, effects of large waves are not detectable within the measurement uncertainty and no noticeable correlation between backscatter coefficients and wave height is found. Under high-wave light-wind conditions, backscatter is enhanced significantly at large incidence angles,with a weaker effect at small incidence angles. Backscatter coefficients in the wind speed range under consideration are compared with SASS-II (Ku band), CMOD3-H1 (C band), and Plant's model results which confirm the experimental observations. Variations of the friction velocity, which can give rise to the observed backscatter behaviors in the presence of large waves, are presented     

TOPEX/Poseidon microwave radiometer (TMR). III. Wet troposphererange correction algorithm and pre-launch error budget

For pt.II see ibid., vol.33, no.1, p.138-46 (1995). The sole mission function of the TOPEX/Poseidon microwave radiometer (TMR) is to provide corrections for the altimeter range errors induced by the highly variable atmospheric water vapor content. The three TMR frequencies are shown to be near-optimum for measuring the vapor-induced path delay within an environment of variable cloud cover and variable sea surface flux background. After a review of the underlying physics relevant to the prediction of 5-40 GHz nadir-viewing microwave brightness temperatures, the authors describe the development of the statistical, two-step algorithm used for the TMR retrieval of path delay. Test simulations are presented which demonstrate the uniformity of algorithm performance over a range of cloud liquid and sea surface wind speed conditions. The results indicate that the inherent algorithm error (assuming noise free measurements and an exact physical model) is less than 0.4 cm of retrieved path delay for a global representation of atmospheric conditions. An algorithm error budget is developed which predicts an overall algorithm accuracy of 0.9 cm when modeling uncertainties are included. When combined with expected TMR antenna and brightness temperature accuracies, an overall measurement accuracy of 1.2 cm for the wet troposphere range correction is predicted     

Simultaneous wind and rain retrieval using SeaWinds data

The SeaWinds scatterometers onboard the QuikSCAT and the Advanced Earth Observing Satellite 2 measure ocean winds on a global scale via the relationship between the normalized radar backscattering cross section of the ocean and the vector wind. The current wind retrieval method ignores scattering and attenuation of ocean rain, which alter backscatter measurements and corrupt retrieved winds. Using a simple rain backscatter and attenuation model, two methods of improving wind estimation in the presence of rain are evaluated. First, if no suitable prior knowledge of the rain rate is available, a maximum-likelihood estimation technique is used to simultaneously retrieve the wind velocity and rain rate. Second, when a suitable outside estimate of the rain rate is available, wind retrieval is performed by correcting the wind geophysical model function for the known rain via the rain backscatter model. The new retrieval techniques are evaluated via simulation and validation with data from the National Centers for Environmental Prediction and the Tropical Rainfall Measuring Mission Precipitation Radar. The simultaneous wind/rain estimation method yields most accurate winds in the "sweet spot" of SeaWinds' swath. On the outer-beam edges of the swath, simultaneous wind/rain estimation is not usable. Wind speeds from simultaneous wind/rain retrieval are nearly unbiased for all rain rates and wind speeds, while conventionally retrieved wind speeds become increasingly biased with rain rate. A synoptic example demonstrates that the new method is capable of reducing the rain-induced wind vector error while producing a consistent (yet noisy) estimate of the rain rate.     

Electromagnetic bias in sea surface range measurements atfrequencies of the TOPEX/Poseidon satellite

Range measurements made by satellite radar altimeters experience an electromagnetic (EM) bias toward the troughs of ocean waves. Measurements taken with the NASA altimeter on the TOPEX/Poseidon satellite in a series of aircraft flights during the Surface Wave Dynamics Experiment (SWADE) indicate that EM bias is slightly higher at 5.3 GHz than at 13.6 GHz, and that the magnitudes of both biases increase with increasing wind speed, as does their difference. Tower, airborne, and satellite measurements show a consistency in the characteristics of the wind speed dependence but suggest that bias decreases with increasing altitude. The airborne measurements appear to be the most reasonable basis for correcting the NASA altimeter range data from the TOPEX/POSEIDON satellite. A preliminary analysis of data acquired at 20.3 m/s in the Southern Ocean Waves Experiment (SOWEX) has given confidence that the quadratic models for the prelaunch EM bias corrections are more appropriate for wind speed dependence than linear models     

A C-Band Wind/Rain Backscatter Model

With the confirmed evidence of rain surface perturbation in recent studies, the rain effects on C-band scatterometer measurements are reevaluated. By using colocated Tropical Rainfall Measuring Mission Precipitation Radar, ESCAT on European Remote Sensing Satellites, and European Centre for Medium-Range Weather Forecasts data, we evaluate the sensitivity of C-band sigmadeg to rain. We develop a low-order wind/rain backscatter model with inputs of surface rain rate, incidence angle, wind speed, wind direction, and azimuth angle. We demonstrate that the wind/rain backscatter model is accurate enough for describing the total backscatter in raining areas with relatively low variance. We also show that the rain surface perturbation is a dominating factor of the rain-induced backscatter. Using three distinct regimes, we show under what conditions the wind, rain, and both wind and rain can be retrieved from the measurements. We find that the effect of rain has a more significant impact on the measurements at high incidence angles than at low incidence angles     

TOPEX/Poseidon Microwave Radiometer (TMR). II. Antenna patterncorrection and brightness temperature algorithm

For pt.I see ibid., vol.33, no.1, p.125-37 (1995). The calibrated antenna temperatures measured by the TOPEX Microwave Radiometer are used to derive radiometric brightness temperatures in the vicinity of the altimeter footprint. The basis for the procedure devised to do this-the antenna pattern correction and brightness temperature algorithm-is described in the paper, along with its associated uncertainties. The algorithm is based on knowledge of the antenna pattern, the ground-based measurements of which are presented along with their analyses. Using the results of these measurements, the authors perform an error analysis that yields the net uncertainties in the derived TMR footprint brightness temperatures. The net brightness temperature uncertainties range from 0.79 to 0.88 K for the three TMR frequencies, and include the radiometer calibration uncertainties which range from 0.54 to 0.57 K. the authors also derive an estimate of the uncertainty incurred by using brightness temperatures measured in the ~40 km TMR footprint to estimate path delay in the ~3 km altimeter footprint. The RMS difference in path delay averaged over the largest TMR footprint relative to that in the altimeter footprint is estimated to be about 0.3 cm. Finally, the authors discuss the error associated with using unequal beams at the three TMR frequencies to derive path delays, and describe an approach using along-track averaging of the algorithm brightness temperatures to reduce this error     

Ku频段卫星雨衰计算及自动观测系统设计

随着Ku频段卫星通信系统的使用,雨衰对卫星传输链路的影响已经成为卫星通信系统设计与使用过程中的重要影响因素。针对雨衰对Ku频段卫星通信系统可用性的影响,首先对雨衰的产生原因及其对卫星传输链路的影响进行了简要介绍,其次对国际电信联盟推荐的雨衰估算方法进行了分析,最后提出了Ku频段卫星链路传输特性自动观测系统的设计方案。     

Time series prediction of rain attenuation from rain rate measurement using synthetic storm technique for a tropical location

A comparison of measured attenuation series with the attenuation series obtained from rain rate measurement by using synthetic storm technique is made for Ku band signal at a tropical location. Validity of the model is tested for the long-term statistics in terms of the cumulative distribution of attenuation occurrence and fade duration. Applicability of the model is also shown to be valid event-wise. It has been demonstrated that the long term statistics of predicted rain attenuation are insensitive to storm translation speed. No significant differences are found when cumulative distributions of predicted attenuation values are compared for different data sampling intervals. It has been observed that there exists a good correlation between the predicted and measured values of attenuation for at least 80% of the events.     

Diurnal variations in rain attenuation on Ku band earth–space paths

This paper presents analytical results of the diurnal variations in Ku band rain attenuation along earth–space paths at four locations in Southeast Asia and proposes a new model that can predict rain fade in a short period of every 2 h daily. Data from four radiometers and four rain gauges over a 3 year period were analysed to obtain the characteristics of diurnal variations in rain attenuation and rainfall as well as cumulative attenuation distributions in every 2 h interval. The results of this analysis are applied to develop an intensive prediction model using the knowledge of rainfall and attenuation statistics. This model is tested with the measured data and is found to be useful for the design of a more efficient Ku band satellite system especially between 99 per cent and 99·9 per cent link availability in an area of heavy rainfall. © 1998 John Wiley & Sons, Ltd.     

Satellite radar altimetry

A brief review of the historical development and principles of satellite radar altimetry is presented, with special emphasis on the unique capability of the microwave altimeter to provide valuable information for global geoscientific studies. Altimeter data over the ocean are used to monitor mean sea levels, wave height, wind speeds, and surface topographical features. Over the ice sheets, the altimeter data are used to produce surface elevation maps, while repeated measurements are used to monitor volume changes. The success of earlier altimeter mission has promoted the development of future missions that will provide more accurate data sets     

中国Ku波段广播通信卫星雨衰减分布

雨衰减对于１０ＧＨｚ以上无线电系统的影响是极为严重的。本文根据我国６５个站点的分钟降雨率数据，利用ＩＴＵ－Ｒ最新给出的雨衰减预报模式，计算出我国未来１２ＧＨｚ三个轨道     

Cloud and Rain Effects on AltiKa/SARAL Ka-Band Radar Altimeter—Part I: Modeling and Mean Annual Data Availability

The AltiKa project, developed by the French Centre National d'Etudes Spatiales, is based on a wideband Ka-band altimeter (35.75 GHz). The technical characteristic of the instrument will offer higher performance both in terms of spatial and vertical resolutions that will lead to the improved observation of ice, coastal areas, inland waters, and wave height. An Indian Space Research Organization satellite, called Satellite with ARgos and AltiKa, will embark the AltiKa altimeter. The launch is scheduled at the end of 2010. The major drawback of Ka-band use is the attenuation of the radar signal by atmospheric liquid water. Clouds and rain effects will thus be a strong constraining factor, because the altimeter link budget imposes an attenuation of less than 3 dB. The impact of rain and clouds on Ka-band altimeter data is analyzed and quantified using an analytical model that computes AltiKa waveforms in the presence of rain or clouds. The results are then used to quantify the waveform attenuation and distortion, as well as the error induced on the altimeter geophysical parameter estimates. Because of the nonlinearity of attenuation relations, the impact of clouds/rain depends more on the cloud/rain variability within the altimeter footprint than on the mean characteristics, which makes correction using coincident rain or cloud data difficult. Small rain cell and small dense clouds can thus strongly distort the waveforms and lead to erroneous geophysical parameter estimates. The probability of 20 Hz and 1-s averaged data loss are computed from the model results and from cloud and rain climatologies. On a global scale, about 3.5% of the 20-Hz data will be lost because of rain and clouds and 2.5% of the 1-s averaged data. However, the probability strongly varies over the global ocean and can exceed 10% in the Tropics.      

A Wind and Rain Backscatter Model Derived From AMSR and SeaWinds Data

The SeaWinds scatterometer was originally designed to measure wind vectors over the ocean by exploiting the relationship between wind-induced surface roughening and the normalized radar backscatter cross section. Rain can degrade scatterometer wind estimation; however, the simultaneous wind/rain (SWR) algorithm was developed to enable SeaWinds to simultaneously retrieve wind and rain rate data. This algorithm is based on colocating data from the Precipitation Radar on the Tropical Rainfall Measuring Mission and SeaWinds on QuikSCAT. This paper develops a new wind and rain radar backscatter model for SWR using colocated data from the Advanced Microwave Scanning Radiometer (AMSR) and SeaWinds aboard the Advanced Earth Observing Satellite II. This paper accounts for rain height in the model in order to calculate surface rain rate from the integrated rain rate. The performance of SWR using the new wind/rain model is measured by comparison of wind vectors and rain rates to the previous SWR algorithm, AMSR rain rates, and National Center for Environmental Prediction numerical weather prediction winds. The new SWR algorithm produces more accurate rain estimates and improved winds, and detects rain with a low false alarm rate.      

长春和新乡雨衰时间序列的马尔科夫链模拟

基于马尔科夫理论建立的N阶马尔科夫链模型,模拟了长春和新乡地区的降雨衰减时间序列,比较了长春和新乡地区单个模拟和实测雨衰时间序列的概率分布;分别统计了长春和新乡地区50组模拟雨衰时间序列的百分概率分布,并与国际电信联盟无线电通信研究组(ITU-R)提供的卫星轨道位置为92°E、频率为12.5GHz在线极化情况下长春和新乡雨区不同降雨衰减值下的时间百分概率进行了比较,一致性很好,从而验证了N阶马尔可夫链模型在中国部分地区的可用性。模拟结果对我国在Ku及以上频段通信卫星的抗衰落技术的发展具有重要的应用价值。