cont'd from OP:
Quote:Observing the atmosphere with RO
The principle of the GNSS-RO technique is based on measuring shifts in phase and amplitude of radio waves as they propagate through the atmosphere from a GNSS satellite — flown at an altitude around 20,000km — to a receiver onboard a polar orbiting satellite — flown at altitudes between 300 and 1,300km (Figure 2). From the perspective of the receiver, a GNSS satellite is seen to set or rise at the Earth’s limb. Receiving a GNSS radio signal over a time-span of about two minutes is enough to make an atmospheric scan from near surface to well above the neutral atmosphere (~100km). During such a scan, the amount of refraction — or bending — of the ray can be computed from the phase shifts, and the refractive index of the air as function of height can be determined. In the upper air, where humidity is low, the refractive index is proportional to air density. Hence, from a single occultation event, a near-vertical profile of temperature, pressure, and density from the middle troposphere to the upper stratosphere can be retrieved.
That is useful information. It does not, however cover the lower troposphere or surface—where we live!
RO is not a panacea:
Quote:Unlike infrared measurements, the RO measurements are not affected by clouds or land-sea differences. Moreover, the RO measurements have a unique long-term stability — the advantage of measuring time differences rather than radiances — and, thus, require no inter-calibration between satellites or instruments. The latter is an important characteristic for studies of the climate where calibration issues can be a limiting factor. The weaknesses of the RO technique include a limited horizontal resolution of a few hundred kilometers, reduced accuracy in the lower troposphere, in particular in the tropics, and that the quasi-random distribution of the profiles makes provision of uniformly gridded data somewhat complicated.
How different this is to the snake oil sellers! Snake oil sellers know they need to skedaddle out of a town etc before the total uselessness of the pablum they sell becomes widely known!
Quote:Preparing RO data for climate studies
Today we have a continuous time-series of more than 20 years of RO measurements, that starts in 2001. These measurements were provided by operational, as well as research, missions. In 2006, the data numbers increased dramatically, first with the launch of the COSMIC Taiwan-United States six-satellite mission, and later, with the launch of EUMETSAT’s Metop satellites that carry the GRAS RO instrument (Figure 3). Currently, these, and other missions operating RO instruments, have provided around 20 million atmospheric profiles that can be used to construct time series for climate applications.
The profiles:
Quote:Daily number of observed atmospheric profiles in version 1 of the ROM SAF CDR and Interim CDR. Data from four RO satellite missions were included in the data records: CHAMP, GRACE, COSMIC, and Metop. The Interim CDR is presently updated regularly with a lag of about one month.
Quote:RO data from GPS receivers operated onboard the CHAMP, GRACE, COSMIC, and Metop missions. The data are provided as four single-mission data records, as well as one multi-mission data record (see data record details below in the section Data used). In the free atmosphere, above about 5–6km, these data records have an excellent stability in time that surpasses that of, eg current reanalysis data records (Gleisner et al., 2020).
Does lee know what reanalysis is? I doubt it, but we will let him read up about it in his own time.
Quote:One factor that needs to be addressed for any satellite-based measurement technique is sampling issues related to the orbits of the satellites. For example, the Metop satellites are placed in sun-synchronous orbits and always pass the equator at the same local time, while other satellites (eg CHAMP, GRACE, COSMIC) slowly drift in local time. As a consequence of the evolution of the observing system, where old satellite missions are gradually replaced by new missions, the local-time coverage may change over time with consequences for observations of, eg the diurnal cycle in the atmosphere. This is handled by a correction for the impacts of sampling errors based on an estimation of those errors. Such sampling-error corrected data are provided as a part the ROM SAF gridded monthly-mean data, and is the preferred choice for studies of climate variability and trends (Gleisner et al., 2020).
Again, pointing out potential problems/errors in the data. This is science, not snake oil.
Quote:An accurate description of climate variability and trends requires time-series that i) are long enough to minimise the effect of variations associated with the weather, the seasons, and any other types of quasi-periodic variability (eg the El Niño-Southern Oscillation (ENSO)), and ii) are long enough to reach the required long-term stability of the measurements. With 20 years of RO data of sufficient accuracy and stability, we are now in a position where RO data contributes to our understanding of the climate of the Earth’s atmosphere (Ringer and Healy, 2008; Gleisner et al., 2022).
cont’d