Abstract
Ground-based microwave radiometers are increasingly used in operational meteorology and nowcasting. These instruments continuously measure the spectra of downwelling atmospheric radiation in the range 20–60 GHz used for the retrieval of tropospheric temperature and water vapor profiles. Spectroscopic uncertainty is an important part of the retrieval error budget, as it leads to systematic bias. In this study, we analyze the difference between observed and simulated microwave spectra obtained from more than four years of microwave and radiosonde observations over Nizhny Novgorod (56.2° N, 44° E). We focus on zenith-measured and elevation-scanning data in clear-sky conditions. The simulated spectra are calculated by a radiative transfer model with the use of radiosonde profiles and different absorption models, corresponding to the latest spectroscopy research. In the case of zenith-measurements, we found a systematic bias (up to ~2 K) of simulated spectra at 51–54 GHz. The sign of bias depends on the absorption model. A thorough investigation of the error budget points to a spectroscopic nature of the observed differences. The dependence of the results on the elevation angle and absorption model can be explained by the basic properties of radiative transfer and by cloud contamination at elevation angles.
Highlights
Today, the improvement of weather forecasting and the increasing predictability of high-impact weather remain the most pressing problems, especially in a changing climate
The MPM2 results are not presented in the plot as they are close to the MPM2a results
We can conclude that due to possible cloud contamination the results presented in Figures 4 and 5 are less valuable in terms of representing spectroscopic error
Summary
The improvement of weather forecasting and the increasing predictability of high-impact weather remain the most pressing problems, especially in a changing climate To address these problems, the new weather forecast models require detailed initial data on three-dimensional spatial distributions of tropospheric characteristics (in particular, temperature, water vapor, and wind) with a relatively high (up to 0.5–1 km) resolution, especially in the low troposphere where satellite data are not suitable. The new weather forecast models require detailed initial data on three-dimensional spatial distributions of tropospheric characteristics (in particular, temperature, water vapor, and wind) with a relatively high (up to 0.5–1 km) resolution, especially in the low troposphere where satellite data are not suitable It became apparent [1,2] that the problem of obtaining such data can be solved by a fairly dense observational network, equipped with cost-effective means to provide continuous measurements of vertical profiles of the thermodynamic characteristics. One of the most promising candidates to feed the weather forecast models is passive microwave remote sensing
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