Implementation and Validation of a Retrieval Algorithm for Profiling of Water Vapor from Differential Attenuation Measurements at Microwaves

The knowledge of the water vapor (WV) distribution in the Earth's atmosphere is of great importance for weather prediction. Meteorological models, in particular, the so-called limited area models, can assimilate humidity measurements, increasing the reliability of the simulated atmospheric dynamics. An important improvement can be achieved, for instance, if we are able to provide the total column with a sufficient precision and accuracy. In this paper, the novel normalized differential spectral attenuation (NDSA) approach is applied to retrieve the vertical profile of WV-and thus the total column-from measurements of differential attenuation signals at microwaves. A forward model (FM) has been used to simulate the ray-tracing of a microwave signal from a transmitter to a receiver in the atmosphere by using the 3-D atmospheric parameters as provided by a numerical weather prediction (NWP) model. From the NDSA measurement, the integrated WV (IWV) content can be directly derived. A further retrieval code is able to invert the measurements of IWV along the path length, providing the vertical humidity profile, which is directly related to the total vertical column assimilated by weather prediction models. In this paper, we show that the values of the total column can be retrieved with a precision and accuracy up to about 0.6% and 2.1%, respectively, which could have a positive impact on NWP models at short time scale.