Abstract
Boundary profile evaluation (BPV) is an approach proposed in order to estimate water vapor content in the atmosphere. It exploits radio occultation (RO) observations of the signals emitted by the satellites of global navigation systems (GNSS) which are eclipsing (rising) as viewed by a low earth orbit satellite (LEO). BPV requires, as a preliminary step, the estimation of the dry background atmosphere model of refractivity (i.e., obtained from bending angle profiles) to be subtracted from the real observations in order to extract water vapor profiles. The determination of the lowest layer of the atmosphere over which the concentration of water vapor can be deemed negligible is particularly crucial for a correct application of the BPV method. In this study, we have applied three methods to set the starting altitudes for the dry air layers of the atmosphere: (1) by air temperature below some threshold values (for example, 250 K); (2) by “smooth” bending angle profiles in ROs; (3) by saturated water vapor pressure. These methods were tested with thermodynamic and bending angle profiles from 912 radiosonde excursions colocated with RO observations. For every dry air starting altitude we determined the best estimator from each of the three methods. In particular, by comparing those estimators with the quantiles and momenta of the dry air starting altitude distributions, we achieved improvements of up to 50% of the humidity profiles.
Highlights
Radio occultation observations continuously measure the deflection angles of anL-band signal (1–2 GHz) from a global navigation systems (GNSS) satellite to a receiver on a low earth orbit satellite (LEO) which is viewing the transmitter in the rising−setting phase behind the Earth’s disk
Working in the context of radio occultation (RO) measurements, such threshold values have to be set according to RO observation accuracies, even if we cannot exclude them, they could find application in other contexts as well. We do this in two ways, depending on whether we measure air humidity by water vapor mixing ratio or by wet refractivity (for a definition of these quantities, see Equations (3) and (10) in Sections 2 and 3, respectively): (1) we define as thresholds those values of water vapor mixing ratios corresponding to significative mean deviations of air dry temperatures and/or pressures from the real ones, where the term significative is related to some statistical considerations; (2) we define as thresholds those values of wet refractivity having the same order of magnitude of the RO dry refractivity uncertainties. Both in (1) and (2) we considered a set of possible threshold values, rather than a single one: we do this because, depending on the particular method one chooses to investigate the thermodynamic properties of the atmosphere, or depending on the site location, different dry air criteria could be most suited for different users
The flipside is that from RO observations alone we cannot predict water vapor concentrations, and RO estimations of atmospheric temperature and pressure lose accuracy in humid air, as we have seen in Figure 3 and Table 1
Summary
L-band signal (1–2 GHz) from a GNSS satellite to a receiver on a LEO which is viewing the transmitter in the rising−setting phase behind the Earth’s disk (see Figure 1). We considered three methods for this task: (1) by (dry) air temperatures exceeding some threshold values (for example, 250 K, as in [39,40]); (2) by the appearance of irregular patterns in the bending angle vertical profiles, as suggested in [41]; (3) by estimating water vapor mixing ratios and wet refractivities via saturated water vapor pressure, this last derived for example by the Murphy−Koop formula [42] Such hypotheses were tested with a statistical study concerning 912 thermodynamic and bending angle vertical profiles of the atmosphere, with the first ones derived from experimental radiosonde data colocated with RO events. A brief analysis of water vapor concentrations in the stratosphere is given in Section 6, while in Section 7 we draw our conclusions
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