Biases caused by the instrument bandwidth and beam width on simulated brightness temperature measurements from scanning microwave radiometers

Abstract

Abstract. More so than the traditional fixed radiometers, the scanning radiometer requires a careful design to ensure high quality measurements. Here the impact of the radiometer characteristics (e.g., antenna beam width and receiver bandwidth) and atmospheric propagation (e.g. curvature of the Earth and vertical gradient of refractive index) on scanning radiometer measurements are presented. A forward radiative transfer model that includes all these effects to represent the instrument measurements is used to estimate the biases. These biases are estimated using differences between the measurement with and without these characteristics for three commonly used frequency bands: K, V and W-band. The receiver channel bandwidth errors are less important in K-band and W-band. Thus, the use of a wider bandwidth to improve detection at low signal-to-noise conditions is acceptable at these frequencies. The biases caused by omitting the antenna beam width in measurement simulations are larger than those caused by omitting the receiver bandwidth, except for V-band where the bandwidth may be more important in the vicinity of absorption peaks. Using simple regression algorithms, the effects of the bandwidth and beam width biases in liquid water path, integrated water vapour, and temperature are also examined. The largest errors in liquid water path and integrated water vapour are associated with the beam width errors.

Validation of brightness and physical temperature from two scanning microwave radiometers in the 60 GHz O<sub>2</sub> band using radiosonde measurements

“…The errors range between −0.3 and +0.1 K. This change from negative to positive bias for the elevation angle was also observed by Meu- (Meunier et al, 2013). Figure 10 shows errors associated with the channel bandwidth effect in Tb differences for different elevation angles.…”

“…While the narrower bandwidths show deviations smaller than 0.2 K, the widest ones reach biases that range between −1.7 and 3 K. Meunier et al (2013) found that overestimations could reach values up to 8.5 and −2.5 K of underestimation for some frequencies with the 1 GHz bandwidth. These large deviations are caused when the peaks of the oxygen individual absorption lines are also covered by the bandwidth of one of the channels.…”

“…The statistical multilinear regression coefficients are obtained from the comparison between the temperature profiles and the simulated Tbs' dataset from the radiosondes. For the HATPRO temperature retrievals, the brightness temperatures measured at the V-band frequencies are used, where the first three frequencies are only used in zenith pointing (51.26,52.28 and 53.86 GHz), and the last four (54.94, 56.66, 57.3 and 58 GHz) are considered for all the elevation angles (Meunier et al, 2013). More details about the atmospheric profiles and the absorption models used in the radiative transfer model can be found in Löhnert and Maier (2012).…”

“…One of the possible reasons that could explain these large discrepancies (larger than for TEMPERA) is that for the HATPRO radiometer the exact centre frequencies and band passes are not known for the instruments analysed in this study (Löhnert and Maier, 2012). Meunier et al (2013) studied the impact of the radiometer characteristics (e.g. antenna beam width and receiver bandwidth) on scanning radiometer measurements, and they found that an inappropriate characterisation of the bandwidth could lead to errors of up to 8 K in the V band.…”

Long-term observations minus background monitoring of ground-based brightness temperatures from a microwave radiometer network

“…This assumption becomes important only at low elevation angles, e.g. up to 1-1.5 K in K-band at 5 • elevation angle (Meunier et al, 2013;Navas-Guzmán et al, 2016).…”