Observed Spatial Variation in Perceptible Water Vapor by a Ground-Based, Dual-Channel Radiometer
Yuei-An Liou
Center for Space and Remote Sensing Research and Graduate Institute of Space Sciences
National Central University
Chung-Li, Taiwan 320,
yueian@csrsr.neu.edu.tw
Abstract
A ground-based water vapor radiometer (WVR) operating at 23.8 and 31.4 GHz was utilized to observe spatial variation in perceptible water vapor (PWW) at the Taipei weather station on March 18-25, 1998. Through a bilinear regression scheme, PWV were inferred from the observed brightness temperatures of the sky at eleven elevation angles from 15° and the corresponding opacities. In order to derive bilinear regression coefficients, radiosonds soundings collected at the Taipei weather station in marches of 1988-1997 were used. Retrieval errors resulting from these coefficients were computed. We found root mean square error (RMSE) (percentage with respect to mean) between the retrieved PWV and those directly obtained from radiosonde soundings to 0.25 cm (6.5%) if a brightness temperature-based retrieval algorithm is used. The corresponding RMSE is reduced to 0.21 cm (5.2%) if an opacity-based retrieval algorithm is utilized. WVR observations show that PWV varies from 2.4 cm for clear sky to 6.5 cm for rainy/cloudy conditions at zenith and that the atmosphere deviates from a spherically-symmetrical assumption by as much as 8.9% at the angle of 165°. WVR-observed PWV differ from radiosonde observations by 0.51 cm if the brightness temperature-based retrieval scheme is used, and 0.49 cm if the opacity-based retrieval scheme is used. The corresponding retrieved PWV averages are 3.41 and 3.33 cm, respectively.
Introduction
Water vapor plays a crucial role in atmospheric dynamics through its dominant influence on the energy balance of the atmosphere. A knowledge of PWV distribution is therefore important to better initialize and constrain numerical weather prediction (NWP) models. The most typical way to measure PWV is by radiosonde soundings, which suffers from the cost of the devices and their limiting use to certain areas of land. Lidars and Fourier transform infrared spectrometers can profile water vapor, but not beyond cloud (Solheim et al., 1998). White solar spectrometer can be used t estimate PWV (Sierk et al., 1998), the technique can only survive in clear days.
Microwave radiometry represents an alternative way to measure PWV of the atmosphere for all-weather conditions. This radiometric approach relies on the fact that the absorption lines of water vapor locate in the microwave region. For example, a combination of 23.8 and 31.5 GHz near 22.235 GHz of water vapor absorption line can be used to determine PWV (Solheim et al., 1998a; Liou, 1998). In this paper, we present PWV observations by a ground-based radiometric approach from a field campaign conducted at the Taipei weather station from March 18 to 25, 1998.
Radioative Tranfer
Radioative transfer equation can be described as (Ulaby, et al., 1981)
where, r is the position function, m, t is the optical depth, No, and J is the source function, W/m
2-sr. Equation (1) can be explained by the Kirchhoff's law which states that under conditions of local thermodynamic equilibrium, thermal emission must be equal to absorption. For upward-looking radiometry, its solution can be written as
Where,
where, k
e is te extinction coefficient of the atmosphere. In the microwave region, Equation (2) by the Rayleigh-Jeans law can be rewritten as
Where, T
bg is the brightness temperature observed by radiometer, K, T
bc represents cosmic brightness temperature (2.7), K, an T
a is the temperature of the atmosphere, K.
PWV Retrievals
To derive multiple regression coefficients, 10-years radiosonde soundings collected at the Taipei weather station, Central Weather Bureau (CWB),in Marches of 1988-1997 were used. The use of monthly climatological data is intended to reduce the influence of seasonal variation on PWV inversions. Radioative transfer model developed by NOAA Wave Propagation Laboratory was applied to compute the brightness temperatures at 23.8 and 31.4 GHz (Schroeder and Wastewater, 1991). The model extrapolates the profiles of water vapor, temperature, and pressure to 0.1 mb while computing atmospheric emission, which is dominated by three key constituents of the atmosphere, namely water vapor, liquid water, and oxygen. The amount of cloud liquid water is derived with an adiabatic assumption when relative humidity is higher than 98% (Liou, 1998). It is found that for the 10-year period the average (standard deviation) is 3.79 cm (0.856 cm) for PWV.
In general, absorption dominates over scattering in the lower portion of the microwave so that the letter can be ignored. Hence, the extinction coefficient in Equations (2) and (4) can be replaced by the absorption coefficient. Since water vapor is of a key parameter to determine the absorption characteristics of the atmosphere, it can be determined by the radiometric observations of the atmosphere. That is
PWV = CPWP0 + CPWV1 x Tb1 + Cpwv2 x Tb2 (5)
where,
- C, are multiple regression coefficients, where the subscript i represents PWV0, PWV1, PWV2, CLW0, CLW1, and CWL2
- Tb, are observed brightness temperatures of the atmosphere, K, where the subscript i= 1 or 2 represents 23.8, and 31.4 GHz, respectively.
For self-consistency, the regression coefficients obtained from the 10-year radiosonde data are used to derive PWV from brightness temperatures at the two frequencies of interest. The retrieved PWV are compared with those derived from radiosonde soundings. We found that the RMSE (percentage with respect to mean) between the retrieved PWV and those derived from radiosonde soundings is 0.25 cm (6.5%). The corresponding RMSE is reduced to 0.21 cm (5.2%) if the opacity-based retrieval scheme is used.
