Radiometric profiling of temperature, water vapor and cloud liquid water using various inversion methods

Abstract

Abstract. We have developed a tunable temperature profiler based on a highly stable synthesizer that can observe at multiple frequencies on the shoulder of the 60-GHz atmospheric oxygen feature. We are developing a similar radiometer to obtain the vertical distribution of water vapor by making observations on the pressure-broadened water vapor line from 22 to 29 GHz. Information on cloud liquid water profiles is also contained in these two wave bands. Various mathematical retrieval methods for temperature, water vapor, and cloud liquid water profiles were tested based on these radiometer designs. These include neural networking, Newtonian iteration of statistically retrieved profiles, and Bayesian "most probable" retrievals. On the basis of realistic radiometer errors and performance, very good retrieval capability is demonstrated. The performance of the various retrieval methods are presented and compared. Examples of profile retrievals are also presented. Data were not binned into seasons to reduce computer time; better retrieval results for all methods would be expected with binning. Copyright 1998 by the American Geophysical UnionPaper number 97RS03656.0048-6604/98/97RS-03656 $11.00 393 ments. They also have the capability to profile cloud liquid water, a capability absent in RAOBs and all other systems except for in situ aircraft devices. Applications for this passive radiometric profiling include weather forecasting and nowcasting; detection of aircraft icing and other aviation-related meteorological hazards; determination of density profiles for artillery trajectory and sound propagation; refractivity profiles for radio ducting prediction; corrections to radio astronomy; satellite positioning and Global Positioning System (GPS) measurements; atmospheric radiation flux studies; estimation and prediction of telecommunication link degradation; and measurement of water vapor densities as they affect hygroscopic aerosols and smokes. Microwave Profiling MethodsThe microwave profiling methods discussed here make use of atmospheric radiation measurements in the 20-to 75-GHz region. The zenith path atmospheric absorption spectrum at sea level for a typical midlatitude atmosphere with a 1-km-thick, 0.5 g/m 3 cloud in this frequency band is shown in Figure 1. The feature at 22.2 GHz is a water vapor resonance that is pressure broadened according to the pressure altitude

An integrated approach toward the incorporation of clouds in the temperature retrievals from microwave measurements

“…However, despite the presence of clouds in many atmospheric observations, only a few studies have dealt with the incorporation of clouds in the temperature retrievals (Löhnert et al, 2004;Solheim et al, 1998;Ware et al, 2003). A better knowledge of cloud characterization as well as of the assessment of its effect on temperature under different cloudy conditions is still needed.…”

Profiling Boundary Layer Temperature Using Microwave Radiometer in East Coast of China

“…The independent vector y contains brightness temperatures in zenith T b zenith and slant path T b slant , surface pressure P , water vapor density ρ, surface temperature T , refractivity N , dry refractivity N d , wet refractivity N w , humidity Rh and integral water vapor content V [14]. The dependent vector x contains the boundary layer temperature profile.…”

“…A variety of techniques can be used to derive the information of the atmospheric state vector x from the observation vector y, which is regarded as radiometric in our case [13][14][15]. In fact, the Forward (F ) problem, represented by the Radiative Transfer Equation (RTE), is not analytically solvable, whose discrete form can be expressed by:…”

Intercomparison of line-parameter spectroscopic databases using downwelling spectral radiance

“…The microwave profiler is also able to perform a 3D scanning of the atmosphere, exploiting both the azimuth and zenith step motors available. The sky brightness temperatures are inverted using a neural network scheme (Solheim et al, 1998) trained on about 10 000 radiosounding profiles. Profiles are output at intervals of 100 m altitude up to 1 km and of 250 m from 1 to 10 km, with a maximum temporal resolution up to 12 s. The system has been proved to retrieve the precipitable water with an accuracy of 0.03 cm (Solheim et al, 1998).…”