Statistical problems of wind-generated gravity waves arising inmicrowave remote sensing of surface winds

The basic geometric features of a developed sea surface affecting the accuracy of wind speed measurements by satellite instruments are reviewed. Based on Seasat scatterometer, Geosat altimeter, and DMSP-SSM/I (Defense Meteorological Satellite Program Special Sensor Microwave/Imager) observations collocated with buoy data, error trends in the satellite winds are shown to be correlated with various measures of wave development. These trends are explained by examining the RMS wave slope of energy-containing waves which, directly or indirectly, affects all microwave techniques. Statistics of temporal-spatial rates of steep and breaking waves (affecting the scatterometer and radiometer measurements) are derived and compared with field observations     

The effects of rain on TOPEX/Poseidon altimeter data

The presence of rain in the sub-satellite track can significantly degrade altimeter measurements by causing an attenuation of the backscattered signal, a change in its path length through the atmosphere and a change in the mean square slope of the sea surface. This can cause errors, not only in the measurement of the satellite altitude, but also in the determination of wind speed and wave height. TOPEX/Poseidon dual-frequency altimeter data (cycles 3 and 8) were searched for instances where the data were possibly degraded by the presence of rain over the North and inter-Tropical Atlantic. A subjective analysis of the data, similar to the one used in previous studies was conducted on the backscatter coefficient, wind speed, significant wave height, sea surface height, TOPEX Microwave Radiometer (TMR) brightness temperatures, liquid water content and data quality flags to identify the orbits possibly affected by rain. From the 105 probable rain events identified, the effects of rain on the TOPEX measurements and data quality parameters were characterized. The strong differential effect of rain on the Ku and C band measurements was then used to define a new rain flag based on a departure from the normal relationship between the C and Ku band backscatter. This new rain flag was shown to detect all the identified rain events, as well as new ones. The TMR rain flag, used operationally, was shown to flag too many altimeter samples and too few rain events, mainly because of its large resolution (few tens of kilometers compared to few kilometers for the altimeter). An estimation of the rainfall rate from the attenuation of the Ku band backscatter was proposed     

Measurement of oceanic wind vector using satellite microwaveradiometers

The possibility of retrieving both wind speed and direction from microwave radiometer measurements of the ocean is studied using Special Sensor Microwave/Imager (SSM/I) measurements collocated with buoy reports from the National Data Buoy Center (NDBC). A physically based algorithm is used to retrieve the wind speed. The RMS difference between the SSM/I and buoy wind speed is 1.6 m/s for 3321 comparisons. It is found that the SSM/I minus buoy wind speed difference is correlated with wind direction. When this wind direction signal is removed, the RMS difference between the SSM/I and buoy winds reduces to 1.3 m/s. The wind direction signal is used to make global, low-resolution maps of the monthly mean oceanic vector. The wind direction sensing capability of a prospective two-look satellite radiometer is also processed     

星载激光测高仪海洋表面回波计算的理论模型

不同地表目标的模拟回波波形对测高仪系统参数设计具有重要意义,而海洋回波参数在Tsai之后很少被研究。根据菲涅耳衍射理论、海洋表面镜面反射性质以及海洋表面波高和斜率的统计规律,推导出与Tsai结果不同的近天顶方向入射时星载海洋测高仪探测器输出的回波解析表达式和回波总光子数;并用该推导结果建立了适用于激光测高仪亚毫弧度量级发散角的回波解析式。将模拟波形与地球科学激光测高系统(GLAS)真实海洋回波做对比,其能量、脉宽、振幅和形状都非常接近,误差均小于6%;分析得出海洋测高仪回波与测高系统参数和海平面上方平均风速有关,以GLAS参数为例,在风速大于12m/s的条件下将很难收到有效海洋回波。该结论对海洋激光测高仪的系统设计参数及海平面上方风速的反演提供了重要的理论依据。     

ERS-1 scatterometer measurements. II. An algorithm forocean-surface wind retrieval including light winds

For pt.I see ibid., vol.36, no.2, p.603-22 (1998). An algorithm for retrieving European Remote Sensing Satellite (ERS-1) scatterometer winds, denoted the Rufenach-Bates-Tosini (RBT) algorithm, is developed and used to retrieve winds collocated within ±25 km of buoy measurements in two oceanic regions, equatorial and midlatitude. An improvement in the retrieved RBT winds over the European Space Agency (ESA) winds is due mainly to a geophysical model employing the full available wind-speed range, including the lightest winds. This model, denoted BMOD5, is tuned by using the scatterometer and buoy measurements, resulting in two different models for the midlatitude and equatorial regions. The RBT retrieved winds exhibit (1) a larger number of solutions (wind vectors) and (2) smaller biases in wind speed than the ESA wind product. The increase in the number of retrieved winds is primarily due to lighter winds employed, 0.2 m/s to 18 m/s; whereas, the ESA winds are truncated near 3 m/s. The ESA winds underestimate the highest winds significantly, by about 20%, and overestimate the lightest winds. The RBT wind bias is less than a few percent at the highest winds and a few tenths of a m/s at the lowest winds. Both algorithms retrieve 180° ambiguous directions almost as often as the true direction. Regression fits to the winds using the RBT algorithm produce standard deviations of 1 m/s and 25° near the equator for winds varying from 0.2-10 m/s and 1.2 m/s and 250 at midlatitudes for winds varying from 0.2-18 m/s, provided that the ambiguities are removed     

Short pulse radar used to measure sea surface wind speed and SWH

A joint airborne measurement program is being pursued by NRL and NASA Wallops Flight Center to determine the extent to which wind speed and sea surface significant wave height (SWH) can be measured quantitatively and remotely with a short pulse (2 ns), wide-beam (60deg), nadir-looking 3-cm radar. The concept involves relative power measurements only and does not need a scanning antenna, doppler filters, or absolute power calibration. The slopes of the leading and trailing edges of the averaged received power for the pulse limited altimeter are used to infer SWH and surface wind speed. The interpretation is based on theoretical models of the effects of SWH on the leading edge shape and rms sea-surface slope on the trailing, edge shape. The models include the radar system parameters of antenna beam width and pulsewidth. Preliminary experimental results look promising and indicate that it may be possible to design a relatively compact airborne radar to infer, in real-time, the sea surface SWH and surface wind speed.     

Evaluation of high-resolution ocean surface vector winds measured by QuikSCAT scatterometer in coastal regions

The SeaWinds scatterometer onboard QuikSCAT covers approximately 90% of the global ocean under clear and cloudy condition in 24 h, and the standard data product has 25-km spatial resolution. Such spatial resolution is not sufficient to resolve small-scale processes, especially in coastal oceans. Based on range-compressed normalized backscatter and a modified wind retrieval algorithm, a coastal wind dataset at 12.5-km resolution was produced. Even with larger error, the high-resolution winds, in medium to high strength, would still be useful over coastal ocean. Using measurements from moored buoys from the National Buoy Data Center, the high-resolution QuikSCAT wind data are found to have similar accuracy as standard data in the open ocean. The accuracy of both high- and standard-resolution winds, particularly in wind directions, is found to degrade near shore. The increase in error is likely caused by the inadequacy of the geophysical model function/ambiguity removal scheme in addressing coastal conditions and light winds situations. The modified algorithm helps to bring the directional accuracy of the high-resolution winds to the accuracy of the standard-resolution winds in near-shore regions, particularly in the nadir and far zones across the satellite track.     

A neural network algorithm for sea ice edge classification

The NASA Scatterometer (NSCAT), launched in August 1995, is designed to measure wind vectors over ice-free oceans. To prevent contamination of the wind measurements, by the presence of sea ice, algorithms based on neural network technology have been developed to classify ice-free ocean surfaces. Neural networks trained using polarized alone and polarized plus multi-azimuth “look” Ku-band backscatter are described. Algorithm skill in locating the sea ice edge around Antarctica is experimentally evaluated using backscatter data from the Seasat-A Satellite Scatterometer that operated in 1978. Comparisons between the algorithms demonstrate a slight advantage of combined polarization and multi-look over using co-polarized backscatter alone. Classification skill is evaluated by comparisons with surface truth (sea ice maps), subjective ice classification, and independent over lapping scatterometer measurements (consecutive revolutions)     

Validating a scatterometer wind algorithm for ERS-1 SAR

The ocean surface wind field is observed from space operationally using scatterometry. The European Space Agency's (ESAs) ERS-1 satellite scatterometer routinely produces a wind product that is assimilated into forecast models. Scatterometry cannot give accurate wind estimates close to land, however, because the field of view of a spaceborne scatterometer is on the order of 50 km. Side lobe contamination, due to the large contrast in backscatter between land and water, compounds the problem. Synthetic aperture radar (SAR) can provide wind speed and direction estimates on a finer scale, so that high-resolution wind fields can be constructed near shore. An algorithm has been developed that uses the spectral expression of wind in SAR imagery to estimate wind direction and calibrated backscatter to estimate wind strength. Three versions, based on C-band scatterometer algorithms, are evaluated for accuracy in potential operational use. Algorithm estimates are compared with wind measurements from buoys in the Gulf of Alaska, Bering Strait, and off the Pacific Northwest coast by using a data set of 61 near-coincident buoy and ERS-1 SAR observations. Representative figures for the accuracy of the algorithm are ±2 m/s for wind speed and ±37° for wind direction at a 25-km spatial resolution     

Measurement of oceanic wind speed from HF sea scatter by skywave radar

Remote measurements of the spatial mean ocean wind speeds were obtained using Doppler spectra resolved to 0.08 Hz from high-resolution HF skywave-radar backscatter measurements of the ocean surface. A standard deviation of 2.4 m/s resulted from the correlation of observed winds over the ocean and the broadening of the Doppler spectra in the vicinity of the higher first-order Bragg line. This broadening, for Doppler spectra unperturbed by the ionospheric propagation, is proportional to the increase in power caused by higher order hydrodynamic and electromagnetic effects in the vicinity of the Bragg line and inversely proportional to the square root of the radio frequency. A lower bound on the measure of wind speed was established at 5 m/s by the low resolution spectral processing and low second-order power. An upper limit is suggested by the steep slope in the region of the sea backscatter spectrum outside the square root of two times the first-order Bragg line Doppler.     

Off-nadir radar altimetry

The characteristics of nadir versus off-nadir altimetry are reviewed and contrasted and a potentially serious problem has been pointed out that has been overlooked by earlier investigators, who focused on the nongeophysical error sources in off-nadir altimetry. Spatial gradients of radar cross section on the sea surface, caused by wind or current gradients or the variation of radar cross section with incidence angle, could introduce significant range errors in off-nadir altimeter. This potentially crippling effect can be overcome by leaving the traditional 13-GHz frequency and implementing the multibeam altimeter at 36 GHz. A multibeam altimeter proposed for the Eos (Earth Observing System) is described as well as a multimode airborne radar altimeter being developed to study problems inherent in off-nadir altimetry     

How Wind Affects Passive Microwave Measurements of Sea Surface Temperature

Uncertainty in the wind speed is a major source of error in passive microwave measurements from satellites of sea surface temperature (SST) because of the non-linear relationship between sea surface emissivity and wind speed. The accuracy of the SST measurement that can be achieved with only passive microwave measurements was assessed by computer modeling. Our investigation showed that the second-order terms must be included in the equation of radiative transfer in an analysis of the errors in the retrieved SST. In addition, we found that the effects of wind roughening and foam production should be treated separately. We have concluded that the accuracy of SST measurements would be improved by including data from an active remote-sensing instrument such as a scatterometer.     

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.     

Comparisons of scatterometer models for the AMI on ERS-1: thepossibility of systematic azimuth angle biases of wind speed anddirection

There have been many different attempts to develop a model to relate the normalized radar backscatter values for the C-band radars of the active microwave instrument (AMI) on ERS-1 as a function of 10-m wind speed, azimuth angle, which is wind direction relative to radar-beam direction and incidence angle. The first two models, namely CMOD-1, Long (1985) and CMOD-2, are analyzed, and modifications of them are used to show by means of Monte Carlo methods that it is important to be able to define the backscatter model for all azimuth angles in addition to obtaining good agreement at upwind, downwind, and crosswind relative to the radar-beam direction. Methods are described to compare one model to another and to show how to systematic discrepancies, which are the result of model differences, can be found. These discrepancies are also expected when various models are employed to recover winds from real backscatter data. Discrepancies between a model and an unknown “true” model can introduce systematic biases in the recovered wind vectors as opposed to random errors, which result from sampling variability. The validation of the vector winds from scatterometer data requires a comparison of these winds with accurate conventionally measured winds. The data buoys deployed by various nations can serve as the appropriate data because ship reports are not accurate enough     

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.     

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     

On airborne measurement of the sea surface wind vector by a scatterometer (altimeter) with a nadir-looking wide-beam antenna

A pilot needs operational information about wind over sea as well as wave height to provide safety for a hydroplane landing on water. Near-surface wind speed and direction can be obtained with an airborne microwave scatterometer, a radar designed for measuring the scatter characteristics of a surface. Mostly narrow-beam antennas are applied for such wind measurement. Unfortunately, a microwave narrow-beam antenna has considerable size that hampers its placement on flying apparatus. In this connection, a possibility to apply a conventional airborne radar altimeter as a scatterometer with a nadir-looking wide-beam antenna in conjunction with Doppler filtering for recovering the wind vector over sea is discussed, and measuring algorithms of sea surface wind speed and direction are proposed. The obtained result can be interesting for many studies in oceanography, meteorology, air-sea interaction, and climate change and for creation of an airborne radar system for amphibious airplane safe landing on the sea surface, in particular for search and rescue operations in coastal areas.     

Retrieval of Ocean Surface Parameters from the Scanning Multifrequency Microwave Radiometer(SMMR) on the Nimbus-7 Satellite

Sea-surface temperature retrievals have been tested on 2 months of Nimbus-7 scanning multichannel microwave radiometer data. Using the prelaunch versions of the instrument calibration and geophysical parameter retrieval algorithms the initial results were poor. Improved algorithms produced substantially better results. It appears that at least for the night-Southern Hemisphere portion of the Nimbus-7 orbit, a rms measurement accuracy of 1.45°C has been achieved. Similar tests with wind speed retrievals yield an accuracy of 2.7 m/s rms with no substantial differences between day and night measurements but limited by availability of surface observations to the Northern Hemisphere. Moreover, it appears that the retrieved wind speed is more nearly related to the square of the wind observed at the surface than to the wind itself.     

The accuracy of preliminary WindSat vector wind measurements: comparisons with NDBC buoys and QuikSCAT

Two preliminary, six-month long global WindSat vector wind datasets are validated using buoys and QuikSCAT measurements. Buoy comparisons yield speed and direction root mean square accuracies of 1.4 m/s and 25/spl deg/ for the "NESDIS0" product and 1.3 m/s and 23/spl deg/ for the more recently produced "B1" product from the Naval Research Laboratory. WindSat along- and across-wind random component errors of 0.7-1.0 and 2.6-2.8 m/s (respectively) are larger than those calculated for QuikSCAT in the same period. Global WindSat-QuikSCAT comparisons generally confirmed the buoy analyses. While simple rain flags based directly on WindSat brightness temperature measurements alone are shown to overflag for rain systematically, the advanced "Environmental Data Record" rain flag in the B1 product matches well with Special Sensor Microwave/Imager rain detection frequency and preserves the accuracy of the unflagged vector wind measurements.     

QuikSCAT geophysical model function for tropical cyclones andapplication to Hurricane Floyd

The QuikSCAT radar measurements of several tropical cyclones in 1999 have been studied to develop the geophysical model function (GMF) of Ku-band radar σ₀ values (normalized radar cross section) for extreme high wind conditions. To account for the effects of precipitation, the authors analyze the co-located rain rates from the Special Sensor Microwave/Imager (SSM/I) and propose the rain rate as a parameter of the GMF. The analysis indicates the deficiency of the NSCAT2 GMF developed for the NASA scatterometer, which overestimates the ocean σ₀ for tropical cyclones and ignores the influence of rain. It is suggested that the QuikSCAT σ₀ is sensitive to the wind speed of up to about 40-50 m s^-1. The authors introduce modifications to the NSCAT2 GMF and apply the modified GMF to the QuikSCAT observations of Hurricane Floyd. The QuikSCAT wind estimates for Hurricane Floyd in 1999 was improved with the maximum wind speed reaching above 60 m s^-1. The authors perform an error analysis by comparing the QuikSCAT winds with the analyses fields from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division (HRD). The reasonable agreement between the improved QuikSCAT winds and the HRD analyses supports the applications of scatterometer wind retrievals for hurricanes