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     

An Ocean Surface Wind Vector Model Function for a Spaceborne Microwave Radiometer

Surface wind vector measurements over the oceans are vital for scientists and forecasters to understand the Earth's global weather and climate. In the last two decades, operational measurements of global ocean wind speeds were obtained from passive microwave radiometers (Special Sensor Microwave/ Imagers); and over this period, full ocean surface wind vector data were obtained from several National Aeronautics and Space Administration and European Space Agency scatterometry missions. However, since SeaSat-A in 1978, there have not been other combined active and passive wind measurements on the same satellite until the launch of Japan Aerospace Exploration Agency's Advanced Earth Observing Satellite-II in 2002. This mission provided a unique data set of coincident measurements between the SeaWinds scatterometer and the Advanced Microwave Scanning Radiometer (AMSR). The AMSR instrument measured linearly polarized brightness temperatures (TB) over the ocean. Although these measurements contained wind direction information, the overlying atmospheric influence obscured this signal and made wind direction retrievals not feasible. However, for radiometer channels between 10 and 37 GHz, a certain linear combination of vertical and horizontal brightness temperatures causes the atmospheric dependence to cancel and surface parameters such as wind speed and direction and sea surface temperature to dominate the resulting signal. In this paper, an empirical relationship between AMSR T_B's (specifically A ^. T_BV - T_BH) and surface wind vectors (inferred from SeaWinds' retrievals) is established for three microwave frequencies: 10, 18, and 37 GHz. This newly developed wind vector model function for microwave radiometers can serve as a basis for wind vector retrievals either separately or in combination with active scatterometer measurements.     

Evaluation of hurricane ocean vector winds from WindSat

The ability to accurately measure ocean surface wind vectors from space in all weather conditions is important in many scientific and operational usages. One highly desirable application of satellite-based wind vector retrievals is to provide realistic estimates of tropical cyclone intensity for hurricane monitoring. Historically, the extreme environmental conditions in tropical cyclones (TCs) have been a challenge to traditional space-based wind vector sensing provided by microwave scatterometers. With the advent of passive microwave polarimetry, an alternate tool for estimating surface wind conditions in the TC has become available. This paper evaluates the WindSat polarimetric radiometer's ability to accurately sense winds within TCs. Three anecdotal cases studies are presented from the 2003 Atlantic Hurricane season. Independent surface wind estimates from aircraft flights and other platforms are used to provide surface wind fields for comparison to WindSat retrievals. Results of a subjective comparison of wind flow patterns are presented as well as quantitative statistics for point location comparisons of wind speed and direction.     

The potential of combining SSM/I and SSM/T2 measurements to improvethe identification of snowcover and precipitation

The potential of passive microwave radiometry for classifying snowcover and precipitation using measurements from the Special Sensor Microwave/Imager (SSM/I) and the Special Sensor Microwave Water Vapor Profiler (SSM/T2) is investigated by modelling the radiative transfer for different surface types and atmospheric conditions. The model accounts for various land surfaces and vegetation covers, different snow types as well as wind roughened ocean water. The atmospheric part includes multiple scattering and depolarization by cloud droplets and precipitating water as well as ice spheres. It was found, that the combination of a window channel (91 GHz) and an atmospheric sounding channel (183±7 GHz) can improve the separation of snowcover and precipitation which is difficult by using only SSM/I channels. The 183±7 GHz channel is strongly influenced by the water vapor distribution which makes its use difficult for warm rain cases and low cloud tops. Then, the signature at this frequency is not unique and the above relation gives no further improvement of the classification. However, the identification of rainfall over cold land backgrounds can be significantly improved, which is illustrated by the application of a combined SSM/I-SSM/T2 algorithm to two satellite datasets when compared to the SSM/I algorithm and to operational surface weather maps     

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     

A nonlinear optimization algorithm for WindSat wind vector retrievals

WindSat is a space-based polarimetric microwave radiometer designed to demonstrate the capability to measure the ocean surface wind vector using a radiometer. We describe a nonlinear iterative algorithm for simultaneous retrieval of sea surface temperature, columnar water vapor, columnar cloud liquid water, and the ocean surface wind vector from WindSat measurements. The algorithm uses a physically based forward model function for the WindSat brightness temperatures. Empirical corrections to the physically based model are discussed. We present evaluations of initial retrieval performance using a six-month dataset of WindSat measurements and collocated data from other satellites and a numerical weather model. We focus primarily on the application to wind vector retrievals.     

High-resolution passive polarimetric microwave mapping of oceansurface wind vector fields

The retrieval of ocean surface wind fields in both one and two dimensions is demonstrated using passive polarimetric microwave imagery obtained from a conical-scanning airborne polarimeter. The retrieval method is based on an empirical geophysical model function (GMF) for ocean surface thermal emission and an adaptive maximum likelihood (ML) wind vector estimator. Data for the GMF were obtained using the polarimetric scanning radiometer/digital (PSR/D) on the NASA P-3 aircraft during the Labrador Sea Deep Convection Experiment in 1997. To develop the GMF, a number of buoy overflights and GPS dropsondes were used, out of which a GMF of 10.7, 18.7, and 37.0 GHz azimuthal harmonics for the first three Stokes parameters was constructed for the SSM/I incident angle of 53.1°. The data show repeatable azimuthal harmonic coefficient amplitudes of ~2-3 K peak-to-peak, with a 100% increase in harmonic amplitudes as the frequency is increased from 10.7 to 37 GHz. The GMF is consistent with and extends the results of two independent studies of SSM/I data and also provides a model for the third Stokes parameter over wind speeds up to 20 m/s. The aircraft data show that the polarimetric channels are much less susceptible to geophysical noise associated with maritime convection than the first two Stokes parameters. The polarimetric measurement technique used in the PSR/D also demonstrates the viability of digital correlation radiometry for aircraft or satellite measurements of the full Stokes vector. The ML retrieval algorithm incorporates the additional information on wind direction available from multiple looks and polarimetric channels in a straightforward manner and accommodates the reduced SNRs of the first two Stokes parameters in the presence of convection by weighting these channels by their inverse SNR     

Validation of Special Sensor Microwave Imager monthly-mean windspeed from July 1987 to December 1989

Since July 1987, wind speed has been routinely computed from first principles, using Special Sensor Microwave Imager (SSM/I) measurements of the intensity of microwave radiation emitted at the ocean surface. The accuracy of monthly-mean SSM/I wind speeds is determined by comparisons with moored-buoy wind measurements. All results for 1988 were virtually identical with 1989. The range of monthly mean moored-buoy wind speeds was 2-10 ms^-1. During 1987, the equatorial matchups were not equivalent with 1988 and 1989, and the cause remains unknown. The root-mean-square (rms) difference of 697 monthly-mean matchups of the composite 1988 and 1989 data set was 1.2 ms ^-1. The rms differences were smaller in the equatorial zone and higher in middle latitudes. At middle latitudes the time series of rms differences displayed an annual cycle. In the equatorial zone the agreement between SSM/I and in situ data was better in regions with a lesser amount of clouds, and vice versa     

Evaluation of late summer passive microwave Arctic sea iceretrievals

The melt period of the Arctic sea ice cover is of particular interest in studies of climate change due to the albedo feedback mechanisms associated with meltponds and openings in the ice pack. The traditionally used satellite passive microwave sea ice concentration algorithms have deficiencies during the summer months due to the period's highly variable surface properties. A newly developed ice concentration algorithm overcomes some of these deficiencies. It corrects for low ice concentration biases caused by surface effects through the use of 85 GHz data in addition to the commonly used 19 and 37 GHz data and, thus, the definition of an additional ice type representing layering and inhomogeneities in the snow layer. This new algorithm will be the standard algorithm for Arctic sea ice concentration retrievals with the EOS Aqua advanced microwave scanning radiometer (AMSR-E) instrument. In this paper, we evaluate the performance of this algorithm for the summer period of 1996 using data from the special sensor microwave imager (SSM/I) which has frequencies similar to the AMSR instrument. The temporal evolution of summertime passive microwave sea ice signatures are investigated and sea ice concentration retrievals from the standard NASA team and the new algorithm are compared. The results show that the introduction of the additional sea ice type in the new algorithm leads to improved summertime sea ice concentrations. The SSM/I sea ice retrievals are validated using SAR-derived ice concentrations that have been convolved with the SSM/I antenna pattern to ensure an appropriate comparison. For the marginal ice zone, with ice concentrations ranging from 40% to 100%, the correlation coefficient of SAR and SSM/I retrievals is 0.66 with a bias of 5% toward higher SAR ice concentrations. For the central Arctic, where ice concentrations varied between 60% and 100%, the correlation coefficient is 0.87 with a negligible bias     

基于笔形波束扫描雷达散射计的海洋表面流测量

为了研究利用雷达散射计进行海洋表面流直接测量的可行性,本文对传统雷达散射计系统参数进行了改进,推导了相关系数模型及去相关因素的表示形式,给出了相位误差模型,并建立了利用雷达散射计进行海洋表面流直接测量的端到端仿真模型.仿真结果表明,在风速大于5m/s的海况条件下,顺轨向和交轨向速度分量标准差可达0.1m/s以下.风速大于7m/s时,可用于海洋表面流反演的刈幅范围大于散射计刈幅宽度的40%.新型散射计的风单元传递误差无论是在低风速还是在高风速条件下均优于扇形波束扫描散射计的风单元传递误差.     

An emissivity-based wind vector retrieval algorithm for the WindSat polarimetric radiometer

The Naval Research Laboratory WindSat polarimetric radiometer was launched on January 6, 2003 and is the first fully polarimetric radiometer to be flown in space. WindSat has three fully polarimetric channels at 10.7, 18.7, and 37.0 GHz and vertically and horizontally polarized channels at 6.8 and 23.8 GHz. A first-generation wind vector retrieval algorithm for the WindSat polarimetric radiometer is developed in this study. An atmospheric clearing algorithm is used to estimate the surface emissivity from the measured WindSat brightness temperature at each channel. A specular correction factor is introduced in the radiative transfer equation to account for excess reflected atmospheric brightness, compared to the specular assumption, as a function wind speed. An empirical geophysical model function relating the surface emissivity to the wind vector is derived using coincident QuikSCAT scatterometer wind vector measurements. The confidence in the derived harmonics for the polarimetric channels is high and should be considered suitable to validate analytical surface scattering models for polarized ocean surface emission. The performance of the retrieval algorithm is assessed with comparisons to Global Data Assimilation System (GDAS) wind vector outputs. The root mean square (RMS) uncertainty of the closest wind direction ambiguity is less than 20/spl deg/ for wind speeds greater than 6 m/s and less than 15/spl deg/ at 10 m/s and greater. The retrieval skill, the percentage of retrievals in which the first-rank solution is the closest to the GDAS reference, is 75% at 7 m/s and 85% or higher above 10 m/s. The wind speed is retrieved with an RMS uncertainty of 1.5 m/s.     

Ocean surface wind speed measurements of the Special SensorMicrowave/Imager (SSM/I)

An operational wind speed algorithm was developed. This algorithm is based on the D-matrix approach, which seeks a linear relationship between measured SSM/I brightness temperatures and environmental parameters. D-matrix performance in the low-to-medium wind speed range was validated by comparing algorithm-derived wind speeds with near-simultaneous and colocated measurements made by the anemometers of offshore ocean buoys. Results indicate that for approximately 85% of the time, the D-matrix-retrieved winds will have an accuracy better than the Defense Meteorological Space Program goal of ±2 m/s. For the remaining 15% of the time, the scene will be rain-flagged and retrieval accuracies will be worse than ±2 m/s     

利用风廓线雷达资料对北京地区边界层日变化特征的分析研究

利用2015年全年AQI和风廓线雷达资料,对北京地区严重污染天气条件下的边界层日变化特征进行分析。结论表明：（1）严重污染天气水平风速很小,尤其在近地面风速接近0 m/s,全天垂直风速分布平均,各层过渡平缓,边界层非常稳定,几乎没有起伏。（2）高浓度污染物的存在阻挡了太阳辐射对地面的传输,同时地表的长波辐射也难以向上扩散,积累到一定程度才会向上发展。缺少热动力使得边界层更加稳定,不利于污染物扩散,形成稳定边界层利于污染天气维持。这一过程形成了污染物与稳定边界层互相促进的恶性循环。（3）风场的动力作用不足,热力湍流起主导作用,湍流强度相比晴空天气要小很多。     

Performance Evaluation of an Operational Spaceborne Scatterometer

Study results are presented showing performance capability of a spaceborne scatterometer to measure ocean surface wind speed and direction operationally. In addition, a research mode is described which will allow development of improved radar signatures for ocean, sea ice, and land targets. The study results show that a scatterometer can meet the operational user requirement of ±2 m/s wind-speed accuracy (or ±10 percent, whichever is greater) and ±20° wind-direction accuracy over most of the expected ocean surface conditions. The six-beam scatterometer design evaluated is shown to be skillful (>90 percent correct) in specifying the correct wind-vector solution (with a 1800° ambiguity) from the multiple solutions derived. Further improvement must rely on meteorological and pattern-recognition techniques which are being studied.     

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.     

An updated analysis of the ocean surface wind direction signal in passive microwave brightness temperatures

We analyze the wind direction signal for vertically (v) and horizontally (h) polarized microwave radiation at 37 GHz, 19 GHz, and 11 GHz; and an Earth incidence angle of 53/spl deg/. We use brightness temperatures from SSM/I and TMI and wind vectors from buoys and the QUIKSCAT scatterometer. The wind vectors are space and time collocated with the radiometer measurements. Water vapor, cloud water and sea surface temperature are obtained from independent measurements and are uncorrelated with the wind direction. We find a wind direction signal that is noticeably smaller at low and moderate wind speeds than a previous analysis had indicated. We attribute the discrepancy to errors in the atmospheric parameters that were present in the data set of the earlier study. We show that the polarization combination 2v-h is almost insensitive to atmospheric changes and agrees with the earlier results. The strength of our new signals agrees well with JPL aircraft radiometer measurements. It is significantly smaller than the prediction of the two-scale sea surface emission model for low and intermediate wind speeds.     

Comparison between cross-track and conical scanning microwavewindow channels near 90 GHz

The principal objective of this study was to determine the angular characteristics of the cross-track 92-GHz window channel of the SSM/T-2 microwave water vapor radiometer (T-2) over the ocean surface and to relate measurements from this instrument to corresponding 85-GHz window channel measurements from the conical scanning SSM/I imager. The conical scanner views at constant incidence angle and fixed polarizations, whereas the cross-track instrument scans across incidence angles with changing polarization. A model, based on radiative transfer calculations and Fresnel surface parameterization, successfully interrelated signals from the two radiometers as a function of T-2 scan angle for a significant fraction of the oceanic measurements. This confirmed the angular dependence model and provided a general relationship between 92-GHz SSM/T-2 and 85-GHz SSM/I signals, which is applicable in the absence of depolarization by rain, clouds, or severe sea surface roughness. Intercomparison between instruments, based on surface modeling, may be useful for instrumental calibration, it may assist in evaluation of microwave transmission models, and it does provide a validity test for ocean surface emissivity parameterization and cloud clearing procedures     

HF radar wave and wind measurement over the Eastern China Sea

High-frequency (HF) radar can be employed to measure sea surface state parameters such as waveheight, wind field, and surface current velocity. This paper describes the application of the HF ground wave radar in remote sensing the surface conditions over the Eastern China Sea in October 2000. The radar, referred to as the OSMAR2000, was developed by Wuhan University. Preliminary wave spectra, waveheights, and wind fields estimated from the collected data are presented and compared with ship-recorded measurements where such are available. The range for wind direction sensing is up to 200 km. Wave information and wind speed can be provided up to a range of 120 km. The mean difference between radar- and ship-measured significant waveheight is 0.323 m; wind direction is measured within 20/spl deg/; and wind speed to within 0.6 m/s. With such agreement being fairly reasonable, the feasibility of the inversion algorithm and the ocean state real-time sensing capability of OSMAR2000 are demonstrated.     

Land-surface-type classification using microwave brightnesstemperatures from the Special Sensor Microwave/Imager

The use of empirical parameter retrieval algorithms over land requires the prior classification of surface types according to their microwave emission properties. A land-surface-type classification scheme was developed to be used with the Special Sensor Microwave/Imager (SSM/I) algorithm package. The classification rules were based on statistical analysis of SSM/I brightness temperature combinations from several surfaces, including dense vegetation, rangeland and agricultural soils, deserts, snow, precipitation, surface moisture, etc. A set of independent classification rules was derived which should result in increased confidence of parameter retrievals     

An evaluation of the potential of polarimetric radiometry for numerical weather prediction using QuikSCAT

It has been proposed that wind vector information derived from passive microwave radiometry may provide an impact on numerical weather forecasts of similar magnitude to that achieved by scatterometers. Polarimetric radiometers have a lower sensitivity to wind direction than scatterometers at low wind speed but comparable sensitivity at high windspeed. In this paper, we describe an experiment which aimed to determine if an observing system only capable of providing wind direction information at wind speeds over 8 ms/sup -1/ can provide comparable impact to one providing wind vectors at wind speeds over 2 ms/sup -1/. The QuikSCAT dataset used in the experiments has a wide swath and is used operationally by several forecast centers. The results confirm that assimilation of wind vectors from QuikSCAT only for wind speeds above 8 ms/sup -1/ gives similar analysis increments and forecast impacts to assimilating wind vectors at all wind speeds above 2 ms/sup -1/. Measurements from the WindSat five frequency polarimetric radiometer are compared with calculations from Met Office global forecast fields, and this also confirms that WindSat measurement and radiative transfer model accuracy appears to be sufficiently good to provide useful information for numerical weather prediction.