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ED R. WESTWATER

Abstract

Vertical temperature profiles of the lower atmosphere are determined from clear air ground-based measurements of microwave thermal emission by oxygen. Angular emission data from two diverse meteorological locations are mathematically inverted by statistical techniques to recover the vertical profiles. Inversion of 52.5 GHz data, gathered at Upolu Point, Hawaii, Hawaii, resulted in an average root-mean-square (rms) difference of 1.27°K between inverted and radiosonde measured profiles from 0 to 10 km. Pressure and humidity profiles are simultaneously estimated from the data; numerical integration of the inverted humidity profiles results in a determination of total vertical water content with a relative accuracy of about 10 percent. Radiometer emission data at 54.0, 54.5, and 55.0 GHz, taken at Salt Lake City, Utah, are inverted with resulting average rms differences of 1.17°K over the height interval from 0 to 6.4 km. A priori temperature variance, corresponding to known surface conditions, is reduced by a factor of 8 to 1. Ground-based thermal inversions are successfully recovered. For both locations, the rms accuracies agree well with predictions based on the theory of statistical estimation.

The statistical inversion equations of Rodgers, and Strand and Westwater are extended for the purpose of inferring profiles from spectrally contaminated radiation measurements. The equations require auto- and cross-covariance matrices of all meteorological variables that contribute to the emission. The general linear estimation equations of Deutsch are applied to a linear approximation to the radiative transfer equation to derive the inversion equations. An analysis of the linearization errors is given.

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Ed R. Westwater and Otto Neall Strand

Abstract

The information content of radiation measurements used in inferring profiles is defined as a reduction in uncertainty in the estimation of a profile after the measurements are introduced. The information is shown to depend directly on the kernel of the equation of radiative transfer, the covariance matrix of experimental error, and the covariance matrix of the a priori statistical information. Calculations based on the minimum rms inversion method are applied to the indirect probing of the vertical temperature distribution by microwave measurements of oxygen thermal emission. Choice of optimum location of measurements is discussed and comparison of the proposed method with that of Twomey is given.

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Viatcheslav V. Tatarskii, Maia S. Tatarskaia, and Ed R. Westwater

Abstract

A new method is presented of statistical retrieval of humidity profiles based on measurements of surface temperature ξ1, surface dewpoint ξ2, and integrated water vapor ξ3. In this method the retrieved values of humidity depend nonlinearly on predictors ξ1,2,3. A self-training algorithm was developed to obtain the values of parameters that enter into the retrieval algorithm. The data from two years of measurements in eight different locations were used for training. The method was applied to an independent dataset (including nonmonotonic profiles) of one month of surface measurements and integrated water vapor obtained from microwave radiometers. Three constraints were imposed: 1) the integrated retrieved humidity profiles had to be equal to the measured values ξ3, 2) the retrieved surface humidity had to coincide with the measured value, and 3) the retrieved humidity had to be positive. The rms deviations of restored humidity values from measured profiles were approximately two times less than natural variations. A limited comparison with conventional linear statistical inversion showed that the nonlinear method may improve the recovery of vertical structure.

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Ying-Hwa Kuo, Yong-Run Guo, and Ed R. Westwater

Abstract

Significant progress has been made over the past decade in the development of remote-sensing instruments to profile wind and temperature. However, the current technology of profiling water vapor remotely is still far from perfect. Although some promising optical research systems, such as the Raman lidar, can provide high vertical resolution profiles of water vapor, it may be years before they are generally available. Currently, there are several systems that can measure the vertically integrated water vapor (i.e., precipitable water) with a high degree of accuracy. In this paper we use a simple method to assimilate precipitable water measurements (possibly from a network of dual-channel ground-based microwave radiometers or a satellite-based system) into a mesoscale model. The basic idea is to relax the predicted precipitable water toward the observed value, while retaining the vertical structure of the model humidity field. We test this method with the special 3-h soundings available from the Severe Environmental Storms and Mesoscale Experiment. The results show that the assimilation of precipitable water into a mesoscale model recovers the vertical structure of water vapor with an accuracy much higher than that from statistical retrieval based on climatology. The improved analysis due to assimilation also leads to improved short-range precipitation forecasts.

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Ed R. Westwater, Michael J. Falls, and Ingrid A. Popa Fotino

Abstract

Dual-channel microwave radiometric measurements of precipitable water vapor are compared with values determined from two types of radiosondes. The first type is used in conventional soundings taken by the National Weather Service. The second is used by the CLASS system, as operated by the National Center for Atmospheric Research. The standard deviations of the two comparisons are nearly equal, being about 0.1 cm, but statistically significant biases occur between the radiometer and the radiosondes. A bias of 0.162 cm is present between radiometer and NWS values during the day and 0.075 cm during the night. The comparison shows that significant differences exist between the radiometer and the NWS moisture soundings when the relative humidity drops below 20 percent for pressures greater than 500 hPa. When this situation occurs, the NWS soundings contain a default dewpoint depression value of 30°C. After such data are removed from the comparisons, agreement between radiometer and NWS radiosonde data is excellent.

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Ed R. Westwater, Wang Zhenhui, Norman C. Grody, and Larry M. McMillin

Abstract

Temperature profiles are derived from ground- and satellite-based microwave radiometric observations. Data taken by the NOAA Profiler during December 1981 to December 1982, at Stapleton International Airport, Denver, Colorado, are combined with NOAA 6/7 Microwave Sounding Unit (MSU) observations over Denver. The results of 460 retrievals by the Profiler, the MSU, and the Profiler + MSU are compared with soundings by National Weather Service radiosondes (RAOBs). From the surface to 300 mb, maximum rms differences between the combined retrievals and RAOBs are less than about 2 K. For 17 cases in March 1981, radiometric data from the Profiler and MSU were combined with tropopause height measurements obtained from a VHF radar. The combined retrievals using the tropopause height information were improved in the vicinity of the tropopause by about 2 K rms relative to the pure passive ones.

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B-C. Gao, A. F. H. Goetz, Ed R. Westwater, J. E. Conel, and R. O. Green

Abstract

Remote sensing of tropospheric water vapor profiles from current geostationary weather satellites is made using a few broadband infrared (IR) channels in the 6–13-µm region. Uncertainties greater than 20% exist in derived water vapor values just above the surface from the IR emission measurements. In this paper, we propose three near-IR channels, one within the 0.94-µm water vapor hand absorption region, and the other two in nearby atmospheric windows, for remote sensing of precipitable water vapor over land areas, excluding lakes and rivers, during daytime from future geostationary satellite platforms. The physical principles are as follows. The reflectance of most surface targets varies approximately linearly with wavelength near 1 µm. The solar radiation on the sun-surface-sensor ray path is attenuated by atmospheric water vapor. The ratio of the radiance from the absorption channel with the radiances from the two window channels removes the surface reflectance effects and yields approximately the mean atmospheric water vapor transmittance of the absorption channel. The integrated water vapor amount from ground to space can be obtained with a precision of better than 5% from the mean transmittance. Because surface reflectances vary slowly with time, temporal variation of precipitable water vapor can be determined reliably. High spatial resolution, precipitable water vapor images are derived from spectral data collected by the Airborne Visible-Infrared Imaging Spectrometer, which measures solar radiation reflected by the surface in the 0.4–2.5-µm region in 10-nm channels and has a ground instantaneous field of view of 20 m from its platform on an ER-2 aircraft at 20 km. The proposed near-IR reflectance technique would complement the IR emission techniques for remote sensing of water vapor profiles from geostationary satellite platforms, especially in the boundary layer where most of the water vapor is located.

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Maia S. Tatarskata, Viatcheslav V. Tatarskii, Valerian I. Tatarskii, and Ed R. Westwater

Abstract

A method of quality control is presented for ground-based, dual-channel microwave measurements of integrated moisture. Such a method is necessary to eliminate spurious data arising from calibration uncertainties, electronic fluctuations, and strong rain and melting snow on the radiometer antenna. The method is based on the prediction of integrated moisture content from surface measurements of temperature and dewpoint temperature. The statistical prediction was based on regression using a carefully screened multiyear training set of surface meteorological observations, and radiosonde and dual-channel radiometric measurements of moisture. Five years of twice-daily data (six years for the summer months) from Denver, Colorado, as well as data obtained from special experiments at Elbert and Platteville, Colorado, formed the training set. Both linear and nonlinear predictions were compared. The method was applied to independent data obtained during 1991–92 experiments at the three locations. The method predicted data quality with a 91% accuracy rate.

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Bo-Cai Gao, Alexander F. H. Goetz, Ed R. Westwater, B. Boba Stankov, and D. Birkenheuer

Abstract

Remote soundings of precipitable water vapor from three systems are compared with each other and with ground truth from radiosondes. Ancillary data from a mesoscale network of surface observing stations and from wind-profiling radars are also used in the analysis. The three remote-sounding techniques are: (a) a reflectance technique using spectral data collected by the Airborne Visible-Infrared Imaging Spectrometer (AVIRIS); (b) an emission technique using Visible-Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS) data acquired from the National Oceanic and Atmospheric Administration's (NOAA) Geostationary Operational Environmental Satellite (GOES); and (c) a microwave technique using data from a limited network of three ground-based dual-channel microwave radiometers. The data were taken over the Front Range of eastern Colorado on 22–23 March 1990. The generally small differences between the three types of rernote-sounding measurements are consistent with the horizontal and temporal resolutions of the instruments. The microwave and optical reflectance measurements agreed to within 0. 1 cm; comparisons of the microwave data with radiosondes were also either that good or explainable. The largest differences between the VAS and the microwave radiometer at Elbert were between 0.4 and 0.5 cm and appear to he due to variable terrain within the satellite footprint.

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Paul E. Racette, Ed R. Westwater, Yong Han, Albin J. Gasiewski, Marian Klein, Domenico Cimini, David C. Jones, Will Manning, Edward J. Kim, James R. Wang, Vladimir Leuski, and Peter Kiedron

Abstract

Extremely dry conditions characterized by amounts of precipitable water vapor (PWV) as low as 1–2 mm commonly occur in high-latitude regions during the winter months. While such dry atmospheres carry only a few percent of the latent heat energy compared to tropical atmospheres, the effects of low vapor amounts on the polar radiation budget—both directly through modulation of longwave radiation and indirectly through the formation of clouds—are considerable. Accurate measurements of PWV during such dry conditions are needed to improve polar radiation models for use in understanding and predicting change in the climatically sensitive polar regions. To this end, the strong water-vapor absorption line at 183.310 GHz provides a unique means of measuring low amounts of PWV. Weighting function analysis, forward model calculations based upon a 7-yr radiosonde dataset, and retrieval simulations consistently predict that radiometric measurements made using several millimeter-wavelength (MMW) channels near the 183-GHz line, together with established microwave (MW) measurements near the 22.235-GHz water-vapor line and ∼31-GHz atmospheric absorption window can be used to determine within 5% uncertainty the full range of PWV expected in the Arctic. This combined capability stands in spite of accuracy limitations stemming from uncertainties due to the sensitivity of the vertical distribution of temperature and water vapor at MMW channels.

In this study the potential of MMW radiometry using the 183-GHz line for measuring low amounts of PWV is demonstrated both theoretically and experimentally. The study uses data obtained during March 1999 as part of an experiment conducted at the Department of Energy’s Cloud and Radiation Testbed (CART) site near Barrow, Alaska. Several radiometers from both NOAA and NASA were deployed during the experiment to provide the first combined MMW and MW ground-based dataset during dry Arctic conditions. Single-channel retrievals of PWV were performed using the MW and MMW data. Discrepancies in the retrieved values were found to be consistent with differences observed between measured brightness temperatures (TBs) and forward-modeled TBs based on concurrent radiosonde profiles. These discrepancies are greater than can be explained by radiometer measurement error alone; errors in the absorption models and uncertainty in the radiosonde measurements contribute to the discrepancies observed. The measurements, retrieval technique, and line model discrepancies are discussed, along with difficulties and potential of MMW/MW PWV measurement.

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