# Review on the Role of GNSS Meteorology in Monitoring Water Vapor for Atmospheric Physics
## 1 Introduction  
Water vapor is a trace gas of the Earth's atmosphere. Despite its relatively low concentration, it is of paramount importance to the Earth's climate. Firstly, water vapor is the major contributor to the natural greenhouse effect and, therefore, in global warming, presents positive climate feedback [1, 2]. It also has an obvious role in the hydrological cycle, and plays a key role in energy transport. Water is evaporated at low latitudes, and its vapor is transported to higher latitudes where, by condensation, it releases high amounts of heat [3]. Water vapor can be quantified using different methods. One of the most common is the integrated water vapor (IWV), which is also known by other names in the literature, such as precipitable water vapor (PWV), precipitable water (PW), integrated precipitable water vapor (IPWV), and so forth. This quantity represents the integral of the concentration of water vapor along the vertical path, and can also be pictured as the height that, in a vessel of a unit cross-section, the water vapor in a column of the same cross-section would reach if all of it condensed to liquid water. The density of liquid water allows the establishment of the equivalence between the superficial concentration (in kg m\({}^{-2}\)) and the height in the vessel (in mm). Another interesting measurement of water vapor is its distribution with height. This distribution can be given as a mixing ratio (grams of water per gram of dry air), as relative humidity, or other measurements of concentration. Global Navigation Satellite Systems (GNSS) allow the retrieval of information about atmospheric water vapor, with different techniques. In this article, we will focus on the ground-based techniques, since GNSS radio-occultation techniques have already been discussed elsewhere [4; 5; 6]. Global Positioning System (GPS) meteorology started when [PERSON] et al. [7] suggested this approach to remotely sensing water vapor, in a time when even GPS, the first GNSS constellation, was not still completed. In that paper, the methodology to derive IWV from tropospheric delay is thoroughly explained. Moreover, some possible applications are depicted. One of them is the obvious use of GNSS-receiver networks to monitor IWV, but also the idea of water vapor tomography by using dense networks is shown. The main idea behind remote sensing of the water vapor through GNSS is that the GNSS signal between satellite and ground-based receiver is delayed by the troposphere, along with other effects. The GNSS processing for obtaining the position of the receiver needs to account for this, which is called slant tropospheric delay (STD). This is usually given in terms of the zenith tropospheric delay (ZTD), since it is not satellite-dependent and, to convert STD to ZTD, a mapping function is needed. Once ZTD is obtained, meteorological data (typically surface atmospheric pressure) are used to compute the non-dipolar component of this ZTD, known as the zenith hydrostatic delay (ZHD). By subtracting the ZHD from the ZTD, only the dipolar component remains, which is exclusively due to the presence of water vapor (because it is the only atmospheric component with permanent dipolar moment). This component is called the zenith wet delay (ZWD). It can be converted to IWV using a factor usually represented by \(\Pi\) (sometimes by Q). The \(\Pi\) factor has been calculated by many methods in the literature (see Section 2.1). The most accurate methods model \(\Pi\) as a function of the weighted mean temperature of the atmosphere, also known as Davis temperature (\(T_{m}\)). One simple way to estimate \(T_{m}\) is through linear regression with surface temperature (\(T_{s}\)). [PERSON] et al. [8] performed a linear regression of \(T_{m}\) and surface temperature (\(T_{s}\)) using radiosonde data in the United States, which is currently known as the Bevis Formula (\(T_{m}=70.2+0.72\cdot T_{s}\)).