Validation of the Surface Air Temperature Products Retrieved From the Atmospheric Infrared Sounder Over China

The Atmospheric Infrared Sounder (AIRS) is the first of a new generation of high spectral resolution atmospheric sounders, which are expected to obtain atmospheric temperature and water vapor profiles with high accuracy. We are interested in investigating the validation of AIRS surface air temperature retrievals, particularly in the region of China. The surface air temperature observations obtained from 540 ground meteorological stations over China were collected, and quantitative comparisons were performed between the AIRS Version 4 retrievals and the ground observations. Then, the main causes of retrieval errors are discussed in detail. Results show that the rms errors of the AIRS surface air temperature retrievals are correlated with the terrain altitudes of the meteorological stations. With the altitude increasing, the rms errors have a trend of gradual increase. The rms errors are insensitive to the ground-observed cloud fraction. With the observed cloud fraction increasing, the small-scale oscillations of rms errors occur. In mountainous and desert regions, the rms errors are larger and can reach up to 11 K sometimes. Furthermore, the AIRS surface air temperature retrievals have better performance in January than in July. In central and eastern China, even the accuracy of accepted quality products in January approaches the goal of the AIRS Team.     

Wind-Vector Retrievals Under Rain With Passive Satellite Microwave Radiometers

We have developed algorithms that retrieve ocean-surface wind speed and direction under rain using brightness-temperature (TB) measurements from passive satellite microwave radiometers. For accurate radiometer retrievals of wind speeds in the rain, it is essential to use TB signals at different frequencies, whose spectral signature makes it possible to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. The wind-speed retrieval accuracy of an algorithm that utilizes C-band frequencies and is trained for tropical cyclones ranges from 2.0 m/s in light rain to 4.0 m/s in heavy rain. We have also trained and tested global algorithms that are less accurate in tropical storms but can be applied under all conditions. The wind-direction retrieval accuracy degrades from about 10$^{circ}$ in light rain to 30$^{circ}$ at the onset of heavy rain. We compare the performance of wind-vector retrievals under rain from microwave radiometers with those from scatterometers and discuss advantages and shortcomings of both instruments. We have also analyzed the wind-induced sea-surface emissivity, including its wind-direction dependence for wind speeds up to 45 m/s.      

Radiometric observations of sea temperature at 2.65 GHz over the Chesapeake Bay

The present work describes the various corrections necessary in order to deduce ocean surface temperature fromS-band microwave radiometer measurements and applies these results to a series of data obtained with a high absolute accuracy radiometer. Measurements made with a 2.65 GHz radiometer from an aircraft flown over the Chesapeake Bay area are presented and compared in detail with accurately obtained sea truth data. For the calm sea, it was found that the observed brightness temperature agreed well with that calculated from the known sea surface and atmospheric properties over a fairly wide range of surface salinity values (0.2 per mille to 25 per mille). For cases where the surface wind speeds are of the order of 7 to 15 knots, an excess brightness temperature was observed which is attributable to surface roughness and microscale surface disturbances. The excess brightness temperature dependence on wind speed was found to correlate to a certain extent with the rms wave slope dependence on wind speed.     

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     

Snow-Cover Parameters Retrieved from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) Data

The Nimbus-7 satellite launched on October 24, 1978, carries a multifrequency, dual-polarized microwave imager. The instrument is designed to sense the ocean surface, the atmosphere, and land surfaces remotely. From previous ground-based and satellite-based microwave experiments, it is well known, that snow cover over land has a very distinct effect on the microwave signatures of the earth surface. It was the goal of this study to show that the three snow-cover parameters: extent, snow water equivalent, and onset of snow melt can be determined using scanning multichannel microwave radiometer (SMMR) data. Our analysis has shown, that the three snow parameters mentioned above are retrievable with sufficient accuracy to be of great value in climatology, meteorology, and hydrology. Snow extent is determined for dry snow cover with depth ?5 cm, snow water equivalent can be determined on a regional basis with ?2 g/cm2 rms accuracy, and the onset of snow melt is clearly visible by the detection of melt and refreeze cycles prior to snow runoff. The algorithms derived are simple enough to be incorporated in fully automated operational data analysis schemes.     

Operational retrieval of cloud-top heights using MISR data

Due to its unique nine-angle configuration, the Multi-angle Imaging SpectroRadiometer (MISR) can retrieve cloud parameters such as cloud-motion vectors and cloud-top heights using a purely geometrical technique that involves locating the same cloud features at different viewing angles. The geometrical nature of this technique means that the retrievals are relatively insensitive to the absolute instrument calibration. Fast stereo-matching algorithms have been developed to perform this image matching automatically on an operational basis. Preliminary results are shown of the operational retrievals together with comparisons against other data. Cloud-top height is generally obtained on a 1.1-km grid with an accuracy of /spl plusmn/ 562 m, even over snow and ice. The limitations of the technique, resulting at times in height blunders, noisy retrievals, and discrete effects of wind correction, are discussed.     

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     

Ocean surface wind speed and direction retrievals from the SSM/I

A semiempirical model is developed that retrieves ocean surface wind direction information in addition to improved wind speeds from Special Sensor Microwave/Imager (SSM/I) measurements. Radiative transfer and neural network techniques were combined in the authors' approach. The model was trained and tested using clear sky cases, but atmospheric transmittance is retrieved so that retrieval in other than clear sky conditions is possible. With two SSM/I instruments currently providing operational ocean surface wind speed retrievals, the addition of wind direction information and improved wind speed retrievals will enhance the impact of this data in weather prediction models and marine weather forecasting     

Antenna Pattern Correction for the Nimbus-7 SMMR

This paper describes the philosophy and method used to develop the antenna pattern correction (APC) algorithm that was used on the data from the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7. There are limitations on what can be accomplished plished with such a procedure; these limitations are explored with the aid of Fourier analysis, even though the algorithm used on the SMMR data does not perform any Fourier transforms. The resulting analysis showed that, for the SMMR instrument, no useful improvement could be made in the data in terms of reduction of side lobes, but the quality of the sea surface temperature retrievals could be improved considerably by matching the antenna beamwidths at the different frequencies.     

Regression Techniques for Oceanographic Parameter Retrieval Using Space-Borne Microwave Radiometry

Variations of conventional multiple regression techniques are applied to the problem of remote sensing of oceanographic parameters from space. The techniques are specifically adapted to the scanning multichannel microwave radiometer (SMMR) launched on the Seasat and Nimbus 7 satellites to determine ocean surface temperature, wind speed, and atmospheric water content. The retrievals are studied primarily from a theoretical viewpoint, to illustrate the retrieval error structure, the relative importances of different radiometer channels, and the tradeoffs between spatial resolution and retrieval accuracy. Comparisons between regressions using simulated and actual SMMR data are discussed; they show similar behavior.     

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.     

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.     

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.     

Selection of optimum frequencies for atmospheric electric path length measurement by satellite-borne microwave radiometers

Numerical experiments using regressions by leaps and hounds have been performed to determine the optimum frequencies for satellite-borne microwave radiometers to estimate atmospheric electrical path length over the sea. The frequency range 5-40 GHz was searched. The effect of surface wind speed, sea surface temperature, and clouds was considered in the optimum frequency selection. Our analysis indicates thatsim 0.6-cm rms accuracy is possible for one-way path length measurement using a proper pair of frequencies. The best two-channel subset selected by the leaps and bounds technique is [16.0, 21.0] GHz.     

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     

A 45-m telescope with a surface accuracy of 65 μm

The Nobeyama 45-m telescope has been upgraded for higher frequency and higher sensitivity observations. The surface accuracy of the antenna was improved from 0.2 mm rms to 65 μm rms using a radio holography method at the prime focus. Pointing accuracy was also improved by replacing a large Gregorian subreflector cabin with a smaller cassegrain subreflector in 1985 to reduce wind loading effects, and by installation of a new master collimator with multi-pole resolvers which were calibrated to an accuracy of 0.4 arcsec rms in 1988. Four SIS receivers using Nb/AlO_x/Nb array junctions are now available on the telescope for 40, 80, 100, and 150-GHz bands. These receivers achieved quite low noise and wide-band tunability. The 2×2 multi-beam receiver for 115 GHz is very powerful for mapping observations. These improvements of telescope performance and these receivers have significantly increased the astronomical observation capability of the telescope in the wide frequency range of 40 to 150 GHz     

SAR-retrieved wind in polar regions-comparison with in situ data and atmospheric model output

European remote sensing (ERS) satellites synthetic aperture radar (SAR) wind retrievals using CMOD-IFR2 are, for the first time, retrieved in the marginal ice zone (MIZ) and in Arctic coastal areas and compared with in situ observations from reseach vessels (RVs) and output from a high-resolution atmospheric model. The root mean squares (rms) of the comparisons were 1.6 m s/sup -1/ and 2 m s/sup -1/, respectively. The spatial variation of the SAR wind fields established a decrease in wind speed close to the ice edge for the late summer situations where the wind was along the ice edge with the ice to the left. This decrease is believed to be due to changes in atmospheric stability, possibly through development of an internal boundary layer caused by the cold ice cover and melt water. Lower wind speed near the ice edge is confirmed by the atmospheric model and the in situ observations. Furthermore, good results are obtained from SAR wind retrieval in leads when compared with model output during a cold-air outbreak. Routine measurements in the MIZ are useful for estimating the wind stress, and therefore SAR may play an important role in this region. Finally, the identification of a jet out from Hinlopen Strait in the Svalbard region and low wind wakes along the coast in the SAR-retrieved wind field is confirmed by in situ observations as the RV moves through the region. The jet is also confirmed by the atmospheric model, which is able to reproduce the situation.     

Evaluation of the haystack antenna and radome

The characteristics of the radome-enclosed Haystack antenna have been evaluated as a radio-astronomical instrument. Important advantages of the radome enclosure are the high pointing precision it permits under all wind conditions, the rms pointing errors being 7" in azimuth and elevation, and the antenna surface tolerance (0.027 in rms) made possible by controlled environment. We searched for but failed to find any detectable radome effects as follows: pointing deviations, gain variations, noise granularity, and polarization effects. The principal electromagnetic effect of the radome is a reduction of aperture efficiency by an amount that varies from about 1 dB at long wavelengths to 2.8 dB at 35 GHz. The noise contribution is about9degK at 8 GHz and21degK at 22.2 GHz.     

Satellite microwave radiometry of forest and surface types inFinland

10.7-, 18-, and 37-GHz data from the Nimbus-7 Scanning Multichannel Microwave Radiometer (Nimbus-7 SMMR) were used to investigate the microwave response to different surface and forest types. SMMR data for the fall seasons of 1978 through 1981 were compared against a digital surface type map that shows seven different surface types for southern Finland and six for northern Finland. For each land-cover category, the brightness temperature behavior as a function of frequency and polarization was determined. The precision of the results is evaluated, and they are compared to other published results. The discrimination of land-cover categories using the brightness temperature is discussed     

N-parameter retrievals from L-band microwave observations acquired over a variety of crop fields

A number of studies have shown the feasibility of estimating surface soil moisture from L-band passive microwave measurements. Such measurements should be acquired in the near future by the Soil Moisture and Ocean Salinity (SMOS) mission. The SMOS measurements will be done at many incidence angles and two polarizations. This multiconfiguration capability could be very useful in soil moisture retrieval studies for decoupling between the effects of soil moisture and of the various surface parameters that also influence the surface emission (surface temperature, vegetation attenuation, soil roughness, etc.). The possibility to implement N-parameter (N-P) retrieval methods (where N = 2, 3, 4, ..., corresponds to the number of parameters that are retrieved) was investigated in this study based on experimental datasets acquired over a variety of crop fields. A large number of configurations of the N-P retrievals were studied, using several initializations of the model input parameters that were considered to be fixed or free. The best general configuration using no ancillary information (same configuration for all datasets) provided an rms error of about 0.059 m/sup 3//m/sup 3/ in the soil moisture retrievals. If a priori information was available on soil roughness and at least one vegetation model parameter, the rms error decreased to 0.049 m/sup 3//m/sup 3/. Using specific retrieval configurations for each dataset, the rms error was generally lower than 0.04 m/sup 3//m/sup 3/.