Analysis of Radiosonde and Ground-Based Remotely Sensed PWV Data from the 2004 North Slope of Alaska Arctic Winter Radiometric Experiment

Abstract During 9 March–9 April 2004, the North Slope of Alaska Arctic Winter Radiometric Experiment was conducted at the Atmospheric Radiation Measurement Program's (ARM) "Great White" field site near Barrow, Alaska. The major goals of the experiment were to compare microwave and millimeter wavelength radiometers and to develop forward models in radiative transfer, all with a focus on cold (temperature from 0° to −40°C) and dry [precipitable water vapor (PWV) < 0.5 cm] conditions. To supplement the remote sensors, several radiosonde packages were deployed: Vaisala RS90 launched at the ARM Duplex and at the Great White and Sippican VIZ-B2 operated by the NWS. In addition, eight dual-radiosonde launches were conducted at the Duplex with Vaisala RS90 and Sippican GPS Mark II, the latter one modified to include a chilled mirror humidity sensor. Temperature comparisons showed a nighttime bias between VIZ-B2 and RS90, which reached 3.5°C at 30 hPa. Relative humidity comparisons indicated better than 5% average agreement between the RS90 and the chilled mirror. A bias of about 20% for the upper troposphere was found in the VIZ-B2 and the Mark II measurements relative to both RS90 and the chilled mirror. Comparisons in PWV were made between a microwave radiometer, a microwave profiler, a global positioning system receiver, and the radiosonde types. An RMS agreement of 0.033 cm was found between the radiometer and the profiler and better than 0.058 cm between the radiometers and GPS. RS90 showed a daytime dry bias on PWV of about 0.02 cm

A tomographic approach to the retrieval of the atmospheric specific attenuation coefficient from measured brightness temperature

The authors propose an inversion scheme devoted to the retrieval of the atmospheric specific absorption coefficient based on data collected by a ground-based microwave radiometer. The technique processes elevation scans. The vertical plan is modelled by allocating M bins in the vertical directions. The forward modelling is defined by linearization of the radiative transfer equation around a reference model of the atmospheric parameter pattern. The goal is to estimate the atmospheric attenuation along the vertical path 3 km away from the radiometer location, where a transponder calibration device for the nadir looking RA-2 altimeter on board of the ENVISAT satellite is positioned. Estimation is performed through inversion of the brightness temperature values observed at different elevation angles, provided a proper parameterization of the model space. According to the agreement of the reference model to the actual conditions two cases are given: either the solution is acceptable or it is not reliable and a different inversion scheme is to be implemented. © 2012 IEEE

On the Use of Microwave Radiometers for Deep Space Mission Applications by Means of a Radiometric-Based Scalar Indicator

The estimation of the path delay due to water vapor is a crucial aspect for the calibration of the Doppler observables of a deep space probe. The advanced water vapor radiometer (AWVR) developed by the Jet Propulsion Laboratory (JPL, NASA) already proved its capability to accurately estimate the path delay during the entire Cassini mission. Here, from the AWVR measurements, a scalar sky status indicator (SSI) was developed as a criterion for selecting the radiometric path delay estimations in the orbit determination process. Results indicate that the use of such index allows a reduction of the range rate residual root mean square (rms)

Geocalibrating millimeter-wave spaceborne radiometers for global-scale cloud retrieval

Millimetre-wave radiometers will be on board of the future operational Eumetsat Polar System Second Generation (EPS-SG) satellites with the primary objective to support weather and climate models. These radiometers, and in particular the Ice Cloud Imager (ICI), will provide channels from 183 up to 664 GHz at a spatial sampling of 16 km, greatly enhancing ice cloud retrieval capability at global scale to validate and improve microphysics parameterization. At millimetre wave the emissivity of surface water bodies increases with frequency with values comparable to land targets so that the ICI brightness temperature contrast between water and land itself diminishes. This ICI feature implies that it is not possible to easily discriminate the surface coastlines, usually exploited for imagery geolocation purposes. This work proposes a methodology to evaluate the expected ICI geolocation error using the 183.3 GHz channel. Data from existing conically-scanning radiometers, such SSMIS (Special Sensor Microwave Imager Sounder), are used to emulate ICI observations. The idea is to extract Earth natural targets with an identifiable contour at 183.3 GHz to be compared with a reference one through a cross-correlation technique in the spatial and spectral domains. Such targets are quite rare and detectable only in dry regions/seasons. One of these regions is here found to be the Antarctic coastlines, which can seasonally change their contour due to temperature variations or ice collapses (creating iceberg). For these Antarctic targets, we propose the use of synthetic aperture radar (SAR) images as reference lines, sufficiently accurate for this purpose thanks to their high spatial resolution. To test this methodology the selected areas are the Ross and Ronne ice shelfs from May to September, the driest period in Antarctica. Ice shelfs are thick suspended platforms of ice with a sufficient brightness temperature contrast to extract the contour of the ice coastline. Using SSMIS data, results will be presented showing the geolocation error sensitivity to spatial resolution and target features. Open issues and future developments will be also discussed

Mapping the atmospheric water vapor by integrating microwave radiometer and GPS measurements

This paper deals with a procedure to generate maps of the integrated precipitable water vapor (IPWV) over the Mediterranean area by using estimates from a global positioning system (GPS) network over land and from the Special Sensor Microwave/Imager (SSM/I) over sea. In particular, we investigate the application of the Kriging geostatistical technique to obtain regularly spaced IPWV values. The horizontal spatial structure of water vapor retrieved by SSM/I is explored by computing variograms that provide a measure of dissimilarity between pairs of IPWV values for the region of interest. Because the water vapor density decreases with height, the GPS station elevation is accounted for in the interpolation procedure. In this respect, the potential of the Kriging with external drift relative to the ordinary Kriging is evaluated by applying a test based on the cross-validation approach. Case studies are presented and qualitatively compared to the corresponding Meteosat infrared images. A quantitative comparison with an independent source of information, such as IPWV computed from radiosonde observations and from European Centre for Medium-Range Weather Forecasts analysis, is also performed.

Satellite-based retrieval of precipitable water vapor over land by using a neural network approach

A method based on neural networks is proposed to retrieve integrated precipitable water vapor (IPWV) over land from brightness temperatures measured by the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). Water vapor values provided by European Centre for Medium-Range Weather Forecasts (ECMWF) were used to train the network. The performance of the network was demonstrated by using a separate data set of AMSR-E observations and the corresponding IPWV values from ECMWF. Our study was optimized over two areas in Northern and Central Italy. Good agreements on the order of 0.24 cm and 0.33 cm rms, respectively, were found between neural network retrievals and ECMWF IPWV data during clear-sky conditions. In the presence of clouds, an rms of the order of 0.38 cm was found for both areas. In addition, results were compared with the IPWV values obtained from in situ instruments, a ground-based radiometer, and a global positioning system (GPS) receiver located in Rome, and a local network of GPS receivers in Como. An rms agreement of 0.34 cm was found between the ground-based radiometer and the neural network retrievals, and of 0.35 cm and 0.40 cm with the GPS located in Rome and Como, respectively

Sun-tracking microwave radiometry: all-weather estimation of atmospheric path attenuation at Ka, V and W band

Sun-tracking (ST) microwave radiometry is a ground-based technique where the Sun is used as a beacon source. The atmospheric antenna noise temperature is measured by alternately pointing toward-the-Sun and off-the-Sun according to a beam switching strategy. By properly developing an ad hoc processing algorithm, we can estimate the atmospheric path attenuation in all-weather conditions. A theoretical framework is proposed to describe the ST radiometric measurements and to evaluate the overall error budget. Two different techniques, based, respectively, on elevation-scanning Langley method and on surface meteorological data method, are proposed and compared to estimate the clear-air reference. Application to available ST radiometric measurements at Ka-, V-, and W-band in Rome (NY, USA) is shown and discussed together with the test of new physically based prediction models for all-weather path attenuation estimation up to about 30 dB at V- and W-band from multichannel microwave radiometric data. Results show an appealing potential of this overall approach in order to overcome the difficulties to perform satellite-to-earth radiopropagation experiments in the unexplored millimeterwave and submillimeter-wave frequency region, especially where experimental data from beacon receivers are not available

Modeling and Predicting Sky-Noise Temperature of Clear, Cloudy, and Rainy Atmosphere From X- to W-Band

A physically-based parametric model (PPM) to predict the sky-noise temperature in all weather conditions is proposed. The proposed prediction model is based on the non-linear regression fit of numerical simulations derived from the sky-noise eddington radiative-transfer model (SNEM) in an absorbing and scattering medium such as gaseous, cloudy and rainy atmosphere. The PPM prediction method, dependent on measured path attenuation, beacon frequency, and antenna-pointing elevation angle, describes the statistical behavior of the atmospheric mean radiative temperature, which in its turn relates sky-noise temperature to slant-path attenuation. PPM validity ranges from X- to W- band and from 10 degrees to 90 degrees in terms of elevation angle. A comparison of the estimated PPM radio-propagation variables with corresponding ITALSAT satellite data, collected at the Spino d'Adda receiving station (Italy), is also carried out and discussed. The PPM prediction technique provides a root-mean-square retrieval error generally less than 8 K for all frequencies. Results show an improvement with respect to the current International Telecommunication Union (ITU) recommendations, especially at Q- and V-band and above, where the atmospheric multiple scattering effects cannot be disregarded