We analyze the seasonal dependency of retrieval error in remote sensing problem while the quantity to be retrieved has seasonal evolution. In particular we estimate the seasonality in tropospheric measurements by HATPRO microwave profiler. For that we employ several methods: estimation using linearized retrieval procedure (employing error analysis), retrieval simulations, and direct comparison of real measurements with radiosonde data from the nearest aerological station.
The atmospheric boundary layer height is a key parameter characterizing this layer. The accurate evaluation of this parameter is critically important for almost all tropospheric research. Recently, remote sensing technique with the use of microwave passive radiometers is widely used for these purposes. IAP RAS performs continuous measurements of troposphere parameters (temperature and water vapor profiles) by the microwave profiler RPG HATPRO-G3. In this work, the dataset obtained during 2013 – 2018 is applied for determining the boundary layer height over Nizhny Novgorod. We compare the results with the estimation of boundary layer height from radiosonde data.
We conduct an analysis of simultaneous measurements of microwave profiler RPGH-HATPRO and radiosonde which were obtained during 2013-2018 observation period. Using microwave data, we quantify the cloudiness of the conditions. We consider two datasets depending on cloudiness: moderate clouds and clear sky. The latter subset of the former. We investigate means and standard deviations of the difference between the temperature profiles retrieved from microwave data and radiosonde profiles. The seasonal means are at least two times the amplitude of whole dataset means. We discuss the reasons for observed behavior.
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